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Category |
Tool |
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Descpription |
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Code & Text |
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Read Single 1D/2D Code |
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Reads a single 1D/2D code from the image – supports formats such as UPC, EAN, Code 39, QR, and others. |
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Read Data Matrix Code |
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Reads a Data Matrix code from the image – a two-dimensional code consisting of black and white squares arranged in a grid pattern. |
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Read Text |
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Detects and reads text in the image – Optical Character Recognition (OCR) for text extraction. |
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Contour |
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Filter |
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Sobel |
Applies the Sobel operator – computes the gradient magnitude and emphasizes edges and intensity variations. |
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Canny |
Applies the Canny edge detection algorithm – detects edges based on intensity gradients in the image. |
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Laplacian |
Applies the Laplace operator – computes the second derivative and enhances areas with rapid intensity changes. |
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Find Contours Basic |
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Detects and outlines contours (white areas) in a binary image – output is sorted by size (from largest to smallest). |
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Find Contours Advanced |
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Detects and outlines contours (white areas) in binary images – requires white objects; output is sorted from largest to smallest. |
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Draw Contours |
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Displays contours on an image – facilitates the identification of object or region outlines. Prerequisite: prior contour detection using “Find Contours.” |
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Get Contour By Index |
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Retrieves contours from a polyline array based on an index range – index is based on the distance from the image origin (0,0). Prerequisite: prior contour detection using “Find Contours.” |
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Get Contour By Area |
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Filters contours by area – sorted from largest to smallest area. Prerequisite: prior contour detection using “Find Contours.” |
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Contours To Region |
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Converts contours into a binary image (region) – can be used as a mask for further processing. Prerequisite: prior contour detection using “Find Contours.” |
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Filter |
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Arithmetic |
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Deviation |
Determines deviations from the target value in the image – highlights areas that differ from the expected pattern. |
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Emphaszie |
Adjusts the contrast and brightness of an image – enhances the display and visibility of details. |
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Sharpening |
Sharpens an image by increasing the contrast between neighboring pixels – enhances details and clarity. |
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Gamma Correction |
Adjusts the gamma value of the image – controls brightness and contrast for optimized display. |
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Substract |
Subtracts pixel values of one image from another – highlights differences between the two images. |
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Pow |
Raises pixel values to a power – increases or decreases brightness to enhance contrast or emphasize details. |
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Smoothing |
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Average |
Applies an average filter – smooths the image and reduces noise or grainy structures. |
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Bilateral |
Applies a bilateral filter – smooths the image while preserving edges by considering spatial distance and intensity differences. |
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Gauss |
Applies a Gaussian filter – smooths the image by averaging pixel values within a Gaussian kernel size. |
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Median |
Applies a median filter – reduces noise by replacing each pixel with the median of its neighborhood. |
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Transformation |
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Anisotropic Scaling |
Scales the width and height of an image by different factors – allows for non-proportional resizing. |
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Isotropic Scaling |
Scales an image uniformly in both directions – maintaining the aspect ratio. |
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Resize |
Resizes an image to specified dimensions – width and height are adjusted precisely. |
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Translation |
Shifts an image horizontally and/or vertically – freed areas are filled with black pixels. |
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Flip |
Flips an image horizontally or vertically – creates a mirror image along the chosen axis. |
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Rotate Center |
Rotates an image by a specified angle – rotation is performed around the center point. |
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Undistort |
Removes the so-called fisheye effect from the image – corrects extreme wide-angle distortions. |
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Image |
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Compare Images |
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Compares two images and highlights differences – deviations appear dark, similarities lighter. |
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Convert to Grayscale |
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Converts an RGB image to grayscale – based on brightness, simplifying color-independent image processing. |
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Crop By Coordinates |
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Crops an image by coordinates – defined by the top-left and bottom-right corners, extracting the desired area. |
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Crop By Shape |
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Crops an image based on a defined shape – selectively extracts the area within that shape. |
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Draw Line Variant |
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Draws a line on the image – useful for marking, highlighting, or annotating in image processing tasks. |
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Draw Shape |
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Enables drawing shapes on the image – ideal for highlighting or marking specific areas. |
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Draw Ellipse |
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Draws an ellipse on the image – useful for annotation, highlighting, or marking specific image areas. |
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Reduce Domain To Shape |
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Limits the image area to a shape without cropping – pixels outside the shape are blacked out, coordinates remain unchanged. |
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Mean |
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Calculates the mean of all pixels – provides information about the average brightness or color intensity in the image. |
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Standard Deviation |
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Calculates the standard deviation of pixel values – indicates how much brightness or color varies or spreads within the image. |
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Miniumum |
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Determines the smallest pixel value in the image – indicates the darkest or lowest intensity area within the entire image. |
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Maximum |
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Determines the highest pixel value in the image – indicates the brightest or most intense area within the entire image. |
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Plot Text |
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Draws text at a specified position on the image – non-displayable characters are replaced with question marks. |
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Get Image Meta Information |
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Provides metadata about the input image – determines image type, width, and height. |
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Split Image (RGB) |
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Determines the RGB color channels of an image – returns one value per channel. |
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Split Image (HSV) |
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Determines the hue, saturation, and brightness of an RGB image – by converting it to the HSV color space and splitting the channels. |
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Combine Image |
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Creates a color image by combining individual images for the red, green, and blue channels. |
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Locate |
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Edge Intersection |
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Determines the intersection point of two segments in the image – optionally displaying the measurement result. |
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Find Single Edge |
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Detects edges in the image – marks strong brightness or color changes, usually at object boundaries or prominent structures. |
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Measure |
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Measure Segment To Segment |
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Measures the shortest, average, and longest distance between two segments – useful for analyzing spatial relationships. |
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Measure Distance (Segment) |
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Measures the distance between a point and a line segment – selectable: shortest distance, or distance to the segment’s start or end point. |
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Measure Distance (Line) |
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Measures the distance between a point and a line – useful for precise positioning relative to the line. |
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Measure Angle (Segment) |
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Measures the angle between two lines – measured counterclockwise from a reference line. |
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Measure Line To Line |
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Measures the distance between two lines – useful for analyzing parallelism or spacing within the image. |
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Measure Angle (Line) |
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Measures the angle between two lines – based on a reference line, measured counterclockwise. |
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Measure Angle (Rectangle) |
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Measures the angle between a line and a side of a non-rectangular rectangle counterclockwise. |
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Calculate Angle |
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Measures the angle between two vectors – measured counterclockwise starting from the reference vector. |
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Region |
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Morphology |
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Erode |
Reduces white areas by removing edge pixels – useful for separating connected objects or removing small spots. |
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Dilate |
Expands white areas by turning edge pixels white – fills gaps and connects broken object parts in the image. |
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Open |
Applies erosion followed by dilation – smooths contours, removes noise, and reliably separates overlapping objects. |
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Close |
Applies dilation followed by erosion – closes gaps, connects object parts, and smooths white areas in the image. |
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Gradient |
Calculates the difference between dilation and erosion – highlights object contours and aids in edge detection. |
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Top Hat |
Calculates the difference between the original image and the opening operation – highlights small bright details such as fine structures or noise. |
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Black Hat |
Calculates the difference between the closing operation and the original image – highlights small dark details such as spots or objects against a bright background. |
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Hit Miss |
Detects specific pixel patterns using two structuring elements – ideal for precise shape and pattern recognition in the image. |
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Area |
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Calculates the area of each white region in the binary image – provides quantitative size information about objects in the image. |
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Center |
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Detects and quantifies connected regions – groups of connected pixels with the same value are considered as individual objects. |
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Count Black Pixels |
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Counts black pixels in the image – useful for determining the size or extent of black areas. |
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Count Regions |
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Detects and counts individual regions – connected pixels with the same value are identified as separate objects. |
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Count White Pixels |
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Counts white pixels in the image – useful for determining the size or extent of white areas. |
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Compare Reigons |
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Merges two regions into one connected region – useful for object recognition, merging, or segmentation evaluation. |
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Concat Region |
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Combines two binary regions using a logical OR – white areas from both images are merged and preserved. |
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Substract |
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Subtracts one region from another (Region1 – Region2) – useful for isolating differences or overlaps. |
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Intersection |
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Compares the intersection of two regions – useful for identifying common areas or features in segmentations. |
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Invert Pixel Region |
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Inverts the pixels of a region – typically white to black and vice versa – for highlighting or creating a negative image. |
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Region To Image |
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Converts a binary region into a grayscale image. |
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Select Region |
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Selects regions based on area, index, height, or width within a specified value range. |
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Select Largest Region |
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Identifies the largest contiguous region – ideal for extracting dominant objects or relevant image areas. |
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Smallest Circle |
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Calculates the smallest circle that completely encloses a region – useful for shape analysis and measurement. |
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Smallest Rectangle |
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Calculates the smallest rectangle that completely encloses a region – useful for analysis and measurement. |
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Region Size |
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Returns the width and height of a region based on the input. |
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Sort Region |
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Sorts regions by X, Y, width, height or area – with specific sorting direction depending on the feature. |
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Sort Contours |
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Sorts contours by X, Y, length, or area; the number of returned contours can be limited. |
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Segmentation |
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Adaptive Threshold |
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Adaptive Thresholding adjusts the threshold locally – ideal for uneven lighting, significantly improves detection accuracy. |
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Binary Threshold |
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Sets pixels below the threshold to zero, and above to 255, i.e. white. |
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To Zero Threshold |
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Sets pixels below the threshold to zero, leaving others unchanged to preserve detail. |
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Color Threshold |
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This node specifically isolates image areas whose pixels lie in a defined color range. |