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