Batch Image Resizer

Fit to Size without Padding

Proportionately resize / scale down an image maintaining aspect ratio until it entirely fits inside the specified dimensions.

Fits to Specific Size No Crop No Padding

Fit to Size and Add Padding

Proportionately resize / scale down an image maintaining aspect ratio until it entirely fits inside the specified dimensions, and add padding when necessary to make sure the resulting image has exactly the specified width and height.

Fits to Specific Size No Crop Adds Padding

Crop to Size

Crop an image to match specified width and height. You can specify where the remaining image region should be located on the original image using alignment and offsets.

Fits to Specific Size Crop No Padding

Fit to Aspect Ratio and Add Padding

Proportionately resize / scale down an image maintaining aspect ratio and adding extra padding as necessary until its resulting size matches a given aspect (width:height) ratio.

Fits to Width:Height Ratio No Crop Adds Padding

Fit to Aspect Ratio and Crop

Crop an image to match specified aspect (width:height) ratio. You can specify where the remaining image region should be located on the original image using alignment and offsets.

Fits to Width:Height Ratio Crop No Padding

Resize by Specified Percentage %

Resize images by either downscaling (shrinking) or upscaling them by the specified percentage of original width or height.

Heads Up! You can restrict resulting image size by specifying Maximum and / or Minimum width and height in pixels.

On the Screenshot the sample image is being proportionately downscaled to just 33% of its original size.

Maintains Proportions

Resize to Specific Width or Height

You can also either downscale (shrink) or upscale an image until one of its sides reaches the desired absolute value in either pixels or print units.

A typical case would be to resize images so that their width is exactly 1000 pixels, with the height being dynamically calculated so that proportions are maintained.

Heads Up! You can restrict resulting image size by specifying Maximum and / or Minimum width and height in percentages (% of original).

On the Screenshot the sample image is being resized so that its width is exactly 400 pixels and the height is proportionately resize with its width.

Maintains Proportions

Adjust Width and Height Independently

Sometimes it may be necessary to change width and height independently of each other.

On the Screenshot the sample image's width is shrunk to only 30% of the original and its height is set to be exactly 450 pixels.

Does Not Maintain Proportions

Change only Width or Height

You can also just modify either width or height only, so that if you modify width, the height will remain unchanged, and vise-versa.

On the Screenshot the sample image's width is shrunk to only 40% of the original while its height is left unchanged, resulting in the final image being stretched vertically.

Does Not Maintain Proportions

Crop to Aspect Ratio

ping to a specified aspect (width:height) ratio is useful when you need to process many images of varying sizes but need to ensure that all resulting images have the same aspect ratio and are of maximum size.

To match a desired aspect ratio, depending on the input image the program will either crop horizontally or vertically.

The alignment option determines if one or both opposing edges will be cropped. For example, if you set alignment to Middle Center, both edges will be cropped, but if you set it to Middle-Left and horizontal crop will be performed, only the right edge will be cropped.

Example In this example, the image is cropped to 4:3 aspect ratio. Because originally it had a bigger aspect ratio, only horizontal edges are trimmed. Both left and right sides are cut because the alignment is set to Center.

Automatically Crop Images

Automatic crop lets you trim images of excess background or padding around the main object or scene.

You can specify background color manually, or the program can automatically deduce it.

You can specify sides to cut, as well as minimum remaining padding per side.

Heads Up! Automatic crop is ideal to quickly remove extra space or padding from multiple images of different sizes having various backgrounds.

Crop to Fixed Region

To crop or clip the image to a rectangle of a fixed size you must specify the size and the alignment of the region of interest in your images.

Alignment can be set precisely using anchors and offsets.

The size can be specified using either pixels, percentages %, or print units like inches and centimeters.

Example In this example, the image is cropped to a box of 60% x 80% (60% of original width, and 80% of original height), and is aligned to the Middle Left.

Crop from the Edges

The simplest kind of crop operation is cropping the image from the specified sides or edges.

You can specify which sides should be cropped and by what amount using pixels, percentages %, and physical units.

Heads Up! You can specify minimum margins and maximum margins using units different from the ones you used for specifying the sides to crop. This allows you to limit cropping when processing multiple images of different sizes, and thus to ensure that all resulting images have a certain minimum width and height. For example, you may set to crop Left and Right by 20% each, at the same time setting Maximum Left and Right margins at 150 pixels; this will ensure that if 20% corresponds to more than 150 pixels, only 150 pixels will be cut.

Example In this example, the image is cropped from the edges as follows: 30% from Left and Right, 20% from the Bottom, and 5 pixels from the Top. Note the different units are used for different sides!

Cut-Out Mid-Section of an Image

Similar to crop, this action lets you remove the specified middle part of an image.

You can precisely control which region is going to be removed using both percentages and pixels to specify both the size of the cut region as well as vertical and horizontal margins.

Flip & Rotate Images

You can flip images manually or according to EXIF orientation tag.

• EXIF-Based Automatic Flip: flip / rotate an image according to EXIF orientation tag
• Flip Horizontally (Mirror): flip an image around central vertical axis
• Flip Vertically (Reflect): flip an image around central horizontal axis
• Rotate by 90°: rotate an image in 90° increments clockwise or counter-clockwise

Rotate Images

You can free-rotate images clockwise and counter-clockwise by the specified amount in degrees.

Because rectangular dimensions increase with rotation, you can:

• Choose to let the canvas grow in order to fit the rotated image in its entirety and set the background color
• Crop the rotated image, so that there is no extra background

Skew Images

Skew images by specified amount (percentages, print units, pixels) in horizontal and/or vertical directions. This is essentially a form of shear mapping.

Affine Transformations with Augmented Matrix

In addition to the Resize, Skew, and Rotate actions you can perform an arbitrary affine transformation with just a single action using augmented matrix.

Torus Wrap

This action produces a torus wrap effect. That is, if an image was a surface of a torus (ring doughnut) and was scrolled either horizontally or vertically while the viewpoint was fixed.

Shrink Images to Fit Specific File Size

Resize (downscale) an image maintaining proportions until it will fit inside a given file size when saved in specified image format with specified options.

On the Screenshot the sample image is proportionately shrunk so that when it is saved as JPEG file with 85% quality, progressive & optimized options it's file will be in the range 47.5 kilobytes to 52.5 kilobytes (specified size is 50 kilobytes with 5% margin of error).

Resize Canvas / Background

This is opposite of crop action. It effectively enlarges the canvas by adding extra space (padding) around the image on specified sides.

On the Screenshot 80 pixels is added to the top side, 10 pixels to the left side, and 10% (relative to original height) are added to the bottom side.

Heads Up! You can specify Minimum and Maximum values for the extra padding. This is useful when the extra padding is specified in percentages (relative to the image's size) but must fall within a specific absolute range in pixels.

9-Slice Constrained Resize

Use this action to stretch or shrink only a specific part of an image while leaving the rest either unaffected.

• First you specify a rectangular region that you want to resize (stretch/shrink width and/or height as you like)
• If the height of the region changes, left & right sides will be either shrunk or stretched
• If the width of the region changes, top & bottom sides will be either shrunk or stretched
• Corners are never affected!
• Affected sides can be either tiled or stretched/shrunk when affected (tiling is recommended for uniform or pattern-based image regions)

On the Screenshot 35% of original image width on a 5% to 40% interval (as viewed from the left) is being shrunk to just 70 pixels; height is not affected. However because width is being selectively reduced it creates an illusion that image is being locally vertically stretched.

HQX Upscaling

Implements HQX upscaling algorithm that allows you to enlarge an image by an integer amount (typically by x2).

In comparison with other resizing actions that use standard resampling (upsampling) methods, this action uses a more specialized algorithm to produce sharper images while avoiding extensive pixelation.

On the Screenshot the image has been enlarged by a factor of 2. While you can see some pixelation, the image appears much smoother than if regular resampling method would have been applied.

Heads Up! This action works best on clip art type images and in conjunction with the Smooth action applied immediately afterwards (to reduce pixelation and blur even more). You can check out advanced, AI-assisted image upscaling at icons8 Upscaler website.

Adjust Contrast

Increase of decrease contrast in your images.

What's unique about it? Only Batch Image Resizer lets you perform per-channel contrast adjustments in any of the 9 supported color models, not just RGB! You can also tweak the mid-point, thus affecting what is considered light and what is considered dark.

Examples For example, you can increase saturation contrast using HSL model, leaving hue and lightness unaffected. Similarly you can, for example, reduce luminosity contrast using CIE Lab color model, leaving a and b channels unaffected.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Contrast Stretch a.k.a. Contrast Normalization

Contrast stretching (also called contrast normalization or histogram stretching) improves the contrast in your images by stretching the range of intensity values they contain to span a desired range of values.

What's unique about it? Only Batch Image Resizer lets you perform per-channel contrast adjustments in any of the 9 supported color models, not just RGB!

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Shadows & Highlights

Increase/decrease shadows (darks) and highlights (lights) in your images.

What's unique about it? Only Batch Image Resizer lets you perform per-channel shadow & highlight adjustments in any of the 9 supported color models, not just RGB! You can also tweak the mid-tones, thus affecting what is considered a "highlight" and what is considered a "shadow".

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Shift Lightness / Luminosity / Luminance

Adjust lightness / luminosity / luminance in your images by shifting its values.

Shifting shifts all pixel values by (adds or subtracts) the specified amount, preserving the difference between different pixels.

On the Screenshot HSL lightness is increased by 20% uniformly everywhere, as can be clearly seen on the histogram underneath the preview.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Scale Lightness / Luminosity / Luminance

Adjust lightness / luminosity / luminance in your images by scaling its values.

Scaling multiplies all pixel values by the specified factor, either amplifying (factor > 1) or reducing (factor < 1) absolute difference between different pixels thus affecting the contrast.

On the Screenshot HSL lightness is scaled by a factor of 1.2, resulting in amplification of the differences in lightness of individual pixels and bigger contrast as can be clearly seen in the preview.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Shift Brightness

Adjust overall brightness of your images by either shifting or scaling brightness values.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Change Intensity

Adjust HSI Intensity of the selected pixels in your images.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Gamma Correction

Perform gamma correction on your images.

What's unique about it? Unlike other software programs Batch Image Resizer lets you adjust gamma on a per-channel basis: you can separately modify Red, Green, and Blue gamma.

Adjust Exposure

To compensate for poor lighting conditions during photo shoots, use adjust exposure feature. It can either brighten dark areas, or darken bright areas, making your photos look natural.

Adjust Luma

Adjust YCbCr Luma values of specified pixels in your images.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Replace Colors

You can replace a single color or a whole range of colors in your images.

You can use tolerance sliders to replace not just a specific single color, but all colors that are "close" to the one specified. This is especially useful in JPEG images, where due to chroma subsampling what was once one color can turn into many different very close colors.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Invert Colors or Channels

You can invert either all colors in the whole image, or only specific channels. In addition, you are not limited to just RGB, you can invert non-RGB channels too: saturation, lightness, etc. This action supports all color models.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Sepia Tone Effect

Apply customizable Sepia filter to make your images look like old photos.

Convert to Grayscale

Convert images to greyscale tone using any of the following methods:

• BT709 R:G:B Ratio
• RMY R:G:B Ratio
• Custom R:G:B Ratio
• HSB Brightness Channel
• HSL Lightness Channel
• HSI Intensity Channel
• YCbCr Luma Channel
• CIE Lab Lightness Channel

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Selective Grayscale

Selectively apply grayscale filter only to colors that fall within a defined range.

Per-channel color tolerance sliders can be used to precisely define the range of affected colors.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Binarization Filter

Binarization is a process of turning a color or grayscale image into strictly 2-color image - typically black & white.

Batch Image Resizer offers several binarization techniques: threshold-based, dithering based, or a combination of the two.

Threshold-based binarization works as follows: colors lighter than a threshold are rendered white, and colors darker than a threshold are rendered black. Some threshold-based methods include: Simple, Otsu, Custom, Iterative, Bradley Local, Threshold with Carry.

Dithering-based binarization works by applying either a default or a custom threshold much like threshold-based binarization, but then dithers the result, mixing it with surrounding pixels. The following dithering methods are supported: Bayer, Burkes, Sierra, Stucki, Floyd-Steinberg, Jarvis-Judice-Ninke.

Tip Use Color Replace action to replace black and white colors to any other colors to create a 2-color image which is not black and white.

Image Palette Color Quantization

You can reduce the number of distinct image colors to 4, 8, 16, 32, 64, 128, or 256. Batch Image Resizer supports the following color quantization algorithms:

• Popularity - Adaptive palette of very good quality using Popularity-Algorithm-Based Quantizer
• Optimal - Optimal palette of acceptable quality.
• Median Cut - Adaptive palette of high quality, using Median Cut Quantizer.
• Octree - Good quality adaptive palette using Octree Quantizer.
• Uniform - Adaptive palette using Uniform Color Quantizer.
• Neu Quant - Produces a high quality, adaptive palette using NeuQuant Neural-Net image quantization algorithm.
• HSL Distinct Selection - Adaptive palette of high quality based on HSL color selection.
• Windows - Very quickly produces a semi-adaptive palette of low quality.
• Xiaolin Wu - Produces an adaptive palette of very good quality.
• Grayscale - Produces a grayscale palette.

Various dithering methods are supported by some of the above color quantizers.

Colorize Effect

Apply colorize filter. This is similar to grayscale filter, except that the image consists of different shades of a specified color instead of gray.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Color Blend Filter

Overlays a specified color on top of the image using one of the 40+ blend modes.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Posterize Effect

With posterize effect you can easily make photos look like more like posters. It works by reducing number of used colors, resulting in sharper color transitions, which in turn creates a poster-like effect.

What's unique about it? Unlike in other software packages, the posterize effect offered by Batch Image Resizer lets you select color model used to reduce number of colors (other programs simply use RGB). This allows you much greater flexibility, as you can, for example, reduce lightness levels to just 5, however keep the number of hue and saturation levels at 15 when using HSL model.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Histogram Equalization

Histogram equalization increases local contrast by better distributing pixel intensities in image histograms, making them more uniformly distributed.

What's unique about it? Unlike other programs, Batch Image Resizer lets you perform histogram equalization on a per-channel basis (instead of on all channels at once) and using color model of your choice! Furthermore you can control equalization strength.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Levels Tool

Levels Tool lets you move, stretch, or compress the intensity levels of your images color channels. Depending on the color model you can adjust brightness, contrast, saturation, hue, tonal range, and other characteristics.

All pixels whose intensity values fall within the specified input range are proportionately "mapped" onto the output range. You can adjust both the minima and the maxima of input and output ranges, as well as their respective mid-points. This works in exactly the same way as Adobe Photoshop Levels tool except applied to the channel(s) of your choice instead of just RGB.

What's unique about it? There are 8 levels tools: one for each supported color model. In addition, you can adjust levels on a per-channel basis (most programs typically only let you adjust all channels together).

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Curves Tool

Similar to levels, the curves tool can take input intensities and selectively stretch or compress them. Unlike levels however, which only has minimum, maximum and midpoint controls, a curve is controlled using any number of anchor points which gives greater flexibility. In effect, curves tool lets you re-map channel's input values onto a different set of output values, making it very similar to Remap Channel action.

What's unique about it? Predefined curve shapes and templates as well as built-in controls make it very easy to come up with the right curve quickly. Unlike other programs, Batch Image Resizer Curves Tool support all color models and channels - not just RGB!

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Color to Alpha

Easily make background color of your images transparent with Color to Alpha action.

• Detects background color automatically
• You can specify background color manually
• Tolerance slider allows for non-uniform backgrounds

On the Screenshot The Yellowish color is manually set to be treated as transparent color. The results can be seen in the preview.

Adjust Opacity

You can decrease or increase the opacity (transparency) of the desired pixels.

On the Screenshot You can see how only the grayish pixels have been made twice as opaque while the blueish pixels' opacity was left unchanged.

Heads Up! All adjustments operate in 2 modes: shifting and scaling. Shifting shifts all pixel values by (adds or subtracts) the specified amount, preserving the difference between different pixels. Scaling multiplies all pixel values by the specified factor, either amplifying (factor > 1) or reducing (factor < 1) absolute difference between different pixels thus affecting the contrast.

Alpha Channel Levels

Another way to adjust opacity of your images is using levels correction as shown here.

All pixels whose intensity values fall within the specified input range are proportionately "mapped" onto the output range. You can adjust both the minima and the maxima of input and output ranges, as well as their respective mid-points. This works in exactly the same way as Adobe Photoshop Levels tool except applied to Alpha channel.

Swap Color Channels

When you swap 2 channels, you replace one by the other, and the other by the one.

On the Screenshot Green and Blue channels of the RGB color model are swapped. Because original image had more greens than blues, the resulting image after channel swapping is the opposite - this is why leaves and grass look violet.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Replace Color Channel(s)

You can replace one channel of one color model by the other channel of the same or different color model.

On the Screenshot The Brightness (Value) channel / component of the HSB/HSV color model is replaced by the Intensity channel of the HSI color model, producing a more pastel-like image.

RGB HSL: Color Model Mixing Allowed

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Mix Color Channels

Channel mixing allows you to tune the intensities of one channel using intensities of the other channels within the same color model.

On the Screenshot Saturation is reduced by 10% uniformly everywhere. Lightness is increased by 25% of Saturation: the more saturated a given pixel is, the more its Lightness will be increased (but only 25% of Saturation value will be used).

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Extract Color Channel

Extracting a color channel produces a grayscale image that represents the pixel values (intensities) within that channel.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Set Color Channel Value

You can set all pixel values within a given range that belong to a specified channel to just a single value.

On the Screenshot All Red intensities > 79 are set to 150. All Blue intensities < 112 are set to 150. You can clearly see the result of this on the histogram below the preview image.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Remap Color Channel

You can manually re-map all values (intensities) within a channel to a different set of values (intensities).

Example If you map 0 to 255, 1 to 254, 2 to 253, etc. on the Red channel, it will be the same as inverting the Red channel. With re-map action however, you can have arbitrary re-mappings.

On the Screenshot Red intensities > 27 and < 90 have been re-mapped to 100. Result can be clearly seen on the histogram below the preview image. Incidentally the same effect can be achieved with the Set Color Channel Value action mentioned on the previous slide.

RGB(A) HSB/HSV HSL HSI HWB YCbCr CIE Lab CIE LCH

Vignette Filter

Applies vignette effect to your images.

What's unique about it? You can achieve vignette effect in 3 distinct ways: by overlaying specified color, by decreasing brightness (intensity) using specified color model's "brightness" channel, or by decreasing alpha-transparency. Choose whichever best fits your needs!

Image Distortion Effects

Batch Image Resizer offers various image distortion effects:

• Waves Effect
• Time Warp Effect
• Moire Pattern Generator
• Swirl / Vortex Effect
• Twist Effect
• Fish Eye Lens Effect
• Sphere Effect
• Bulge Effect

On the Screenshot Wave Effect makes your images look wavy. You can control wave's with, height, and strength.

Smooth Filter

Smooths images by making jagged edges more rounded.

Tip Smoothing is not the same as blurring! Blurring diffuses pixels and does not preserve edges. Smoothing, on the other hand preserves edges and only removes jaggedness and sharpness; it does not diffuse pixels.

Edge Detection Filters

Batch Image Resizer offers several edge detection filters.

Basic edge detection methods include:

• Quick
• Emboss
• Horizontal
• Vertical

Some edge detection techniques allow you to specify a threshold:

• Homogeneity
• Difference
• Sobel
• Prewitt
• Kirsh

Additionally there are edge-enhancement-related actions: Edge Enhance, and Outline.

Other Morphological Operations

Among other morphological operations supported by Batch Image Resizer are: Bottom Hat, Top Hat, and Hit & Miss Filtering.

• Bottom Hat subtracts the original image from the result of Closing operation. It allows to get all object parts, which were added by Closing, but were not removed after that due to formed connections.
• Top Hat subtracts original image from the result of Opening operation. It allows to get all object parts which were removed by Opening, but were never restored.
• Hit and Miss is a generalization of Dilation and Erosion morphological operations.

File Information Condition

Check if the file being processed matches specified file properties such as name pattern, location, size, and attributes.

The following checks can be performed by this condition:

• File name and extension match a predefined pattern (either wildcards or RegEx)
• File's parent directory matches a predefined pattern (either wildcards or RegEx)
• File's full path matches a predefined pattern (RegEx only)
• File's size is within specified range: at least N bytes, at most N bytes, exactly N bytes, between N and M bytes, not equal to N bytes
• File's creation, change, and access dates are within specified range
• File's attributes match supplied values

Image Size Condition

Check if the image being processed matches specified size (dimensions) such as width and height.

The following checks can be performed by this condition:

• Image width and height are within specified ranges
• Image overall area (pixel count, width x height) matches specified range
• Image aspect ratio (width : height) falls within specified range
• Image has a certain orientation: Landscape, Portrait, or Square
• Image has a given horizontal and/or vertical resolution (in dpi)

Face Detection Condition

Check if the image being processed contains any matching human faces.

• Specify required number of faces
• Specify required face size, and size variation/range
• Specify face orientation (tilt)
• Specify various accuracy settings
• Ability to select a rectangular region where faces should be looked for
• Optional ability to use cloud-based face recognition provided by Microsoft (entirely optional and should only be used if built-in face detection results are poor).

RGBA Levels Condition

Check if the image being processed has certain color characteristics as determined by the RGB color model.

First, RGBA histogram is computed for the specified rectangular region (or by default the whole image). Then that histogram is evaluated against specified Red, Green, Blue, and Alpha intensity ranges using a selected statistic: mean, median, minimum, maximum, or specified percentage of pixels.

This allows you to perform highly fine-tuned processing with different actions and/or options being applied to different images depending on, for example, their Redness, or the amounts of Blue.

• Specify Red, Green, Blue, and Alpha intensity ranges
• Specify statistic to check for each range: Minimum, Maximum, Average (Mean), Midpoint (Median), Specified Percentage of all pixels
• Specify rectangular region to check (by default whole image is checked). Use rectangular region setting if some of your images have a logo in a particular place. This will allow you to split images into 2 groups: those with logo and those without logo automatically, so you can perform different actions on each!

Color Levels Condition

First, a histogram is computed for the specified rectangular region (or by default the whole image). Then that histogram is evaluated against specified component intensity ranges that depend on the selected color model using a selected statistic: mean, median, minimum, maximum, or specified percentage of pixels.

This allows you to perform highly fine-tuned processing with different actions and/or options being applied to different images depending on, for example, their Brightness, or Saturation.

• RGBA, CMY, HSL, HSV, HSI, HWB, CIE Lab, CIE LCH, YCbCr models
• Specify component intensity ranges: Hue, Saturation, Luminosity, etc. (depends on the selected model)
• Specify statistic to check for each range: Minimum, Maximum, Average (Mean), Midpoint (Median), Specified Percentage of all pixels
• Specify rectangular region to check (by default whole image is checked). Use rectangular region setting if some of your images have a logo in a particular place. This will allow you to split images into 2 groups: those with logo and those without logo automatically, so you can perform different actions on each!

Metadata Condition

Check if a given image file has or does not have a specified metadata.

The following checks can be performed by this condition:

• Presence or absence of the following metadata: Comments, EXIF, EXIF Specific, EXIF GPS, EXIF MakerNote, EXIF Interop, IPTC, XMP, Geo TIFF
• EXIF Orientation specification: one of 8 possible values

Palette Condition

Check the bit depth of an image as well as transparency type (if any).

The following checks can be performed by this condition:

• Palette type (color count): 64-bit color, 48-bit color, 32-bit color, 24-bit color, 16-bit color, 16-bit grayscale, 8-bit indexed, 4-bit indexed, 1-bit indexed, any
• Transparency type: none, simple, alpha-transparency, any
• Transparent color (for indexed palettes)

Image Format Condition

Check actual format of the image. This does a detailed image format check by actually inspecting the image file itself instead of just looking at the file extension.

The condition allows you to specify allowed and disallowed image formats by putting a check-mark next to the allowed ones.

Condition Behavior Settings

Every condition has these common behavior settings that determine how it interacts with other conditions and thus how it affects image processing flow.

• Condition may allow further processing either if the requirements / check specified by it are met or not met (i.e. if the result of checking the image against a constraint is either True or False).
• Condition group behavior determines whether the conditions add to each other (i.e. each condition in a group adds additional requirements — equivalent to logical AND, or if the processing should continue as long as at least one condition in a group will pass — equivalent to logical OR.
• In addition it is possible to compare conditions inside a group using logical XOR operator, and negate the entire condition check.
• Negation of a condition or a condition group result may be very useful, because some times it is easier to define the checks for the True case and not for the negated case.

Manual Processing Mode

In Manual Mode the program processes images only upon explicit initiation (when you add images, and click on the Start button).

Images can be added to the processing list in a variety of ways:

• Images can be selected individually
• All images from a particular folder can be added in one click
• Recursively scan directories and look for images that match given criteria
• Drag and drop from Windows Explorer / Folder / Desktop
• Import from a text-based list of file paths
• Paste from clipboard
• Open from previously saved file list
• Directly from Windows by selecting images in Windows Explorer, right-clicking, and launching the program that way (selected images will be automatically added)

Manual Mode Image List Management

In Manual Mode you can sort and filter images in various ways. This way you can quickly select only those images that match desired criteria.

Images can be sorted within the processing list in a variety of ways:

• By their file attributes like name and size
• By image size like width, height, overall size, resolution
• Color diversity - number of unique colors
• Color properties: brightness, saturation, even hue

Ability to filter and sort images by their color-related properties is unique to Batch Image Resizer and you will not find it in other programs.

Clicking on an image thumbnail will take you to the Preview Mode where you will be able to see how the processed image will look like after all the actions you have defined were applied.

Processing in Manual Mode

When images are processed in Manual Mode, a detailed progress is displayed right within the image list, letting you know which imagea are being processed and what is the processing stage

Once the image has been processed, its thumbnail along with preview will be automatically updated to reflect any changes. Attributes that have been changed will be shown in bold making it easy for you to spot changes. The color of the thumbnail will reflect the status: green means no errors, while orange or red indicate warnings and errors during processing, in which case you can click on the log icon that appears to see a detailed processing log for the image and figure out what went wrong.

In addition, you can easily filter the image list by processing result status. For example, you may remove all successfully processed images with just one click, leaving only those that had issues or were skipped.

Automatic Processing Mode

In Automatic Mode, instead of selecting specific images for processing, you setup "monitors" that tell the program which images should be processed and when; and the processing is performed automatically and continually when the specified conditions are met.

3 Types of Monitors

The program supports 3 kinds of monitors: File Exists, File Added, and File Changed. Depending on the kind of monitor you setup, the processing will be triggered only when appropriate condition is met.

For example, if you set up a File Exists monitor, the program will always process all qualified images in the monitored folder as long as they are present; however if you set up a File Added monitor, the program will process only the new images that have been copied to or moved to the folder since the start of its monitoring.

How Monitors Work

The monitors work by continually scanning the specified folder (directory) and subfolders for specified images that match a predefined naming pattern (mask) as well as other properties. The scanning happens at equally spaced time intervals that you define (refresh rate).

Among the file properties that may be examined are: file size, file dates, file attributes. In addition a variety of image-specific properties can be examined: image dimensions, aspect ratio, color depth, EXIF meta-data, etc. Thus Batch Image Resizer will enqueue for processing only those images that match all the requirements specified in the monitor.

Monitors List

After a monitor has been set up, it will appear in the list of monitors.

You can define as many monitors as you like subject to the system resources you have and the product edition that you are using. Additionally, monitors can be enabled and disabled with a single click.

You can also save and open monitor lists easily, so you can reuse your monitor setups later.

Processing in Automatic Mode

In automatic mode processing works in 2 stages. First, the monitor(s) scan the specified folder(s) for any valid images, and add them to the processing queue. Then the program automatically processes all the images in that queue. These 2 stages need not be consecutive, as the program begins processing as soon as the queue is non-empty.

Unlike in the Manual Mode, in the Automatic Mode you can pause processing, make the changes to the actions in the actions sequence and / or the monitors, and then resume.

Triggered / Scheduled Processing Mode

In Triggered or Scheduled Processing Mode, image processing is started upon a specified event (trigger) or at a specific time as per the specified schedule.

You can create as many triggered/scheduled processing jobs as you want - all with different schedules, files to process, actions to perform, and other settings.

Batch Image Resizer need not be running in order for the processing jobs to be activated, the program and processing is started automatically by Windows Task Scheduler Service.

Creating Processing Jobs

Creating a processing jobs is straight forward. You define some general settings such as job's name, mode of operation. Then you specify the job's schedule or trigger that will determine when the processing job is actually ran. Finally you specify the which images should be processed; how the images should be processed (which actions should be performed); and where the processed images should be saved.

Managing Processing Jobs

Once the processing job has been created, it appears in the list of processing jobs. This list reflects all the jobs that have been created and are registered with Windows Task Scheduler Service which is responsible for job's execution.

Jobs can be enabled and disabled with a single click by putting or removing the checkmark next to the job's name in the list.

Specify Destination Folder

Processed images can be saved to:

• Original folder
• An existing folder given by absolute path
• An existing folder given by relative path
• A folder given by dynamic path, which may include over 100 different dynamic tags like image width, height, EXIF data, original folder, etc. If the generated path does not exist, it will be created automatically.

Use Tags to Generate Dynamic File Names

You can save processed images under either the original or the new file name. Batch Image Resizer can automatically generate new file name according to the pattern you specify. This pattern may include literal characters, as well as over 100 built-in dynamic tags that will be automatically replaced with appropriate content at run time.

Program features a built-in File Name Designer with simple drag & drop user interface that lets you select various tags from a large list and use these tags as part of the generated file name.

The tags may represent either dynamically generated content that can be included as part of the file name, or a command that somehow modifies the part of the filename that has already been generated (like changing letter case, or performing replacement operation).

More than 100 Tags!

There are more than 100 different tags that can be used to generate dynamic file names that meet your requirements. Simply include the tag in the appropriate place in the file name pattern to have dynamically generated content inserted in the right place (if the tag generates content), or to affect the generated filename in other ways (if the tag represents a command or operation).

The following tags are available:

• File creation and modification dates, file size
• Current date and time
• Random numbers and letters
• Image properties: width, height, size, bit depth, resolution
• File hashes: MD5, SHA1, SHA2, CRC…
• Original file name, extension, folder name
• EXIF and IPTC tags
• Search & Replace operation letting you replace text within file name
• RegEx Replace - replace within file names using Regular Expressions
• Letter case modification commands (make upper case, lower case)

Recursive Image Search

One of the ways you can add images to the image list for processing is by doing a search for all images that match criteria you specify. The program will scan selected directories and subdirectories for any valid images and automatically add them to the list.

• Recursive scanning with customizable depth
• Specify files to include and exclude using highly customizable patterns and masks - much more powerful than your basic wildcards but easier to use than Regular Expressions!
• Specify directories to exclude from search
• Use Regular Expressions to specify file name patterns
• Use case sensitive matching

Note that you can save your customized image searches as templates for future use.

Search for Files Based on Properties

You can find images you need for processing based on file properties like size or creation date, and attributes. This is in addition to basic search by name!

What's more is that you can fine tune these and select the exact ranges for all properties, like setting the size to be between 1MB and 5MB for example. With dates, too, you can be as specific as you want: you may, for example, look for files created on any day in May 2020, or on May 10 2020 specifically.

Find Images Matching Certain Attributes

You can search for and add images for processing using not just their file names and file properties, but actual image properties as well!

Search for images based on their attributes:

• Width and Height
• Area (Pixel Size)
• Aspect Ratio
• Orientation: Landscape, Portrait, Square
• Horizontal and Vertical Resolution
• Bit Depth and Palette Type
• Transparency Type and Color
• Actual Image File Format: JPEG, PNG, BMP, etc...
• Metadata EXIF, IPTC, GPS, XMP, etc...

Find photos with Faces

With built-in face recognition it is possible to automatically find and add for processing only those images that have human faces in them.

You can select from various options like: face size and orientation, face count, etc.

It is possible to use an optional cloud-based face recognition provided by Microsoft if you are not satisfied with the detection results provided by built-in face recognition.

Pixel-Based Image Search

You can search for and add files for processing using their content - that is using their pixels! Maybe you are looking for grayscale or highly desaturated images in a folder that contains various images. Or perhaps you need to find images with a particular dominant hue. These tasks are possible with pixel based image search!

For each image examined, a histogram is computed for the specified rectangular region (or by default the whole image). Then that histogram is evaluated against specified component intensity ranges that depend on the selected color model using selected statistic: mean, median, minimum, maximum, or specified percentage of pixels.

• RGBA, CMY, HSL, HSV, HSI, HWB, CIE Lab, CIE LCH, YCbCr models
• Specify component intensity ranges: Hue, Saturation, Luminosity, etc. (depends on the selected model)
• Specify statistic to check for each range: Minimum, Maximum, Average (Mean), Midpoint (Median), Specified Percentage of all pixels
• Specify rectangular region to check (by default whole image is checked).

Tip Use rectangular region setting if some of your images have a logo in a particular place. This will allow you to add either only the images with a logo or those without logo automatically!

Filter Images In/Out of Your List

You can use built-in Image Filter with identical functionality to the Image Search feature. This allows you to easily remove from the list or select all matching images that are already in your list!

Setup a Processing Job - General Properties

Processing jobs allow you to setup various batch image processing tasks that will be executed on a specified trigger or on schedule.

General properties include: name of the job, general timeframe when the job can be active, operation mode that determines if any UI will be shown, and user account together with security context under which the job will be executed.

Setup a Processing Job - Select Images

There are several ways in which you can specify which images should be processed by a processing job:

• Specified directories will be scanned for files matching a given name pattern
• Specified image search template will be used (see Recursive File Search)
• Specified list of files containing files' full paths will be used.

Setup a Processing Job - Specify Actions

Once you have specified which images should be processed by a processing job, the next step is to specify how these images should be processed, which actions and operations should be performed. This is done by specifying a previously saved Action Sequence.

Additionally you can customize a few other processing aspects like the number of processing threads and logging options.

Setup a Processing Job - Output Settings

Output settings determine where and how the processed images are saved. All the options that are available in Step 3 in Manual and Automatic processing modes can be customized here as well. These include:

• File naming pattern and destination / output folder
• Image File Format and parameters
• Ability to define a third-party tool to execute after processing has finished
• Backup- and file saving- related options

Setup a Processing Job - Triggers

Last step in setting up a processing job is to define a trigger or specify a schedule that will determine when the processing job will actually execute.

The following triggers are available:

• Monthly - job executed on a monthly basis
• Weekly - job executed on a weekly basis
• Daily - job executed daily at a specified time or every specified time interval
• Event-Driven - job executed on a certain trigger like a given system event

Setup a Processing Job - Command Line Preview

A processing job is automatically executed by the means of Windows Task Scheduler Service launching the program on appropriate trigger / schedule and with job-specific command line arguments.

The Command Line Preview tab shows you the exact command line that will be run in order to start the processing job. That way you can launch the program manually with appropriate parameters and have the same processing job be manually started.

Preview Action Effects

Before you process images you can preview either currently selected action or all actions in the action sequence on the preview image of your choice.

You can toggle Side-by-Side view as shown here, or you can view only the modified version of the image.

You can also toggle histogram below that will display color counts for the displayed image in one of the supported color models.

Preview Image Format Options

You can also preview the results of saving an image using a particular image format and its format-specific options like JPEG's quality setting.

It not only shows resulting file size but preview the actual image so you can select appropriate quality by judging how the result looks.