Image

Creates a depth image from the Z-values of the input surface.

Allows for performing 2D operations on 3D data.

Creates an image filled with one color.

Most typically used to prepare a background for image drawing tools.

Extracts the image content (raw pixel data) as a binary buffer.

Returns an interpolated single pixel of an image.

Sub-pixel sampling of an image.

Returns an array of pixel values at specified locations; the image range is checked.

Returns one of the 9 characteristic points of an image (corners or mid-points).

Creates an image by joining an array of 1D profiles into consecutive image rows.

Usually used for merging 3D profiles into a depth image.

Converts a pixel array to a single-channel image.

Creates a new image with a standard pitch alignment.

Can be used to normalize an image created with a non-standard third-party camera or framegrabber.

Sets a pixel of an image to the selected value.

Sets pixel values in a single entire row of an image.

Allows for creating images from calculated real values.

If the input image contains at least one pixel, then it is copied to the output; otherwise Nil is returned.

Secures against domain errors caused by empty images.

Converts a Bayer-encoded color image into RGB color space.

Use this filter only if the conversion functionality is not provided by the camera (check appropriate pixel types).

Converts color space from Hue-Saturation-Intensity into Red-Green-Blue.

Converts color space from Hue-Saturation-Value to Red-Green-Blue.

Converts a RGB555 image into a RGB888 one.

Decompression of pixel depth from 2 to 3 bytes.

Converts a RGB888 image into a RGB555 one.

Compression of pixel depth from 3 to 2 bytes.

Converts color space from Red-Green-Blue into Cyan-Magenta-Yellow-Key.

CMYK color space is designed for printing - not recommended for machine vision.

Converts color space from Red-Green-Blue to Hue-Saturation-Luminance.

Color analysis is easier in the HSL color space than in RGB.

Converts color space from Red-Green-Blue to L*a*b*.

Converts color space from Red-Green-Blue into pseudointensitY-Orange-Green.

Converts color space from Red-Green-Blue into YUV.

Converts color space from XYZ to Red-Green-Blue.

XYZ color space is designed for human perception - not recommended for machine vision.

Converts color space from pseudointensitY-Orange-Green into Red-Green-Blue.

Converts color space from YUV into Red-Green-Blue.

Adds images of an array pixel by pixel.

Averages two images pixel by pixel.

Averages images appearing in consecutive iterations pixel by pixel.

Takes pixels from the first image within the specified region and from the other one elsewhere.

Computes the non-negative distances between corresponding pixel values using tiles.

Useful for things like comparing an image against a template or for detecting differences between consecutive video frames.

Divides two images pixel by pixel.

Can be used for flat field correction.

Interpolates two images linearly pixel by pixel according to another image values.

Computes the maximum of images of an array pixel by pixel.

Compute median value for each pixel of images from an array.

Computes the minimum of images of an array pixel by pixel.

Multiplies two images pixel by pixel.

Multiplies images appearing in consecutive iterations pixel by pixel.

Averages images appearing in an array pixel by pixel using exponential rolling average.

Subtracts two images pixel by pixel. The result is signed.

Creates a monochromatic image by summing the values of the input image channels with saturation.

Creates a monochromatic image by averaging the input image channels.

Creates a monochromatic image by averaging the input image channels.

Conversion to mono which is more consistent with human perception (our eyes are more sensitive to green).

Changes the type of pixel components.

Creates a monochromatic image by taking the maximum value of all the input image channels.

Creates a monochromatic image by taking the minimum value of all the input image channels.

Reverses the order of channels in an image.

E.g. when one has an RGB image, but needs to convert to BGR.

Creates several monochromatic images from individual channels of the input image.

Draws arcs on an image with multiple colors.

Draws arcs on an image with two colors, depending on the status of each arc.

Usually: green or red for pass/fail status.

Draws boxes on an image with a single color.

Draws circles on an image with multiple colors.

Draws circles on an image with two colors, depending on the status of each circle.

Usually: green or red for pass/fail status.

Draws coordinate systems on an image with a single color.

Draws crosshairs on an image with multiple colors.

Draws crosshairs on an image with two colors, depending on the status of each crosshair.

Usually: green or red for pass/fail status.

Draws dimension lines on an image with a single color.

Draws ellipses on an image with multiple colors.

Draws ellipses on an image with two colors, depending on the status of each ellipse.

Usually: green or red for pass/fail status.

Draws an image on another one.

Draws a grid of images.

Draws lines on an image with a single color.

Draws paths on an image with multiple colors.

Draws paths on an image with two colors, depending on the status of each path.

Usually: green or red for pass/fail status.

Draws points on an image with a single color.

Draws rectangles on an image with multiple colors.

Draws rectangles on an image with two colors, depending on the status of each rectangle.

Usually: green or red for pass/fail status.

Draws regions on an image with a single color.

Draws segments on an image with multiple colors.

Draws segments on an image with two colors, depending on the status of each segment.

Usually: green or red for pass/fail status.

Draws shape regions on an image with a single color.

Draws strings (text) on an image with multiple colors.

Draws strings (text) on an image with two colors, depending on the status of each string.

Usually: green or red for pass/fail status.

Draws strings (text) on an image with a single color.

Draws vectors at associated initial points on an image with multiple colors.

Draws vectors on an image with two colors, depending on the status of each vector.

Usually: green or red for pass/fail status.

Colorizes heat-map and blends it with background image.

Adjusts image colors by stretching each channel separately.

Speculatively sets pixel values outside of a region using the fast marching method and coherence analysis.

Fills in a region of an image with pixel values interpolated from the borders of the area.

Speculative setting of unknown (or unwanted) pixels. Usually used for preparing incomplete images for further processing.

Fills in a region of an image with pixel values interpolated from the borders of the area; uses fast marching method.

Speculative setting of unknown (or unwanted) pixels. This version is trying to do this better than with simple interpolation.

Normalizes local brightness of the image. Internally uses Gauss smoothing.

Compensates uneven illumination.

Normalizes local contrast of the image using Wallis filter.

Computes an image in which the pixel values denote the estimated distances to the nearest bright pixel in the input image.

This is an initial step of some advanced traditional image analysis algorithms.

Finds ridge pixels in a gradient image.

Computes the histogram of the image pixel values.

Finds image locations characterized by locally minimal pixel values.

Detection of characteristic points, usually after some image transformations.

Computes the selected moment of an image in regular and normalized (divided by sum of pixel values) variant.

Returns an array of pixels from the input image.

Creates a series of segments across the input path, measures the average pixel intensity on each of the segments, and creates the final profile from those values.

This is the first step of all 1D Edge Detection operations. Here available for direct use by the user.

Finds ridge pixels in an image.

Calculates standard deviation of image pixel values.

Scans a disk directory for image files and then returns the images one by one in consecutive iterations sorted randomly.

Emulates image acquisition with images stored on disk.

Simulates capturing a frame from a camera.

Can be used as EnumerateImages, but its state is global in a program - does not reset when some task is finished.

Loads a single image format from a file without loading all image data.

Loads a image array from a tiff file.

Saves an image to a file stored in ByteBuffer.

Use this filter if you want to send image file through I/O communication, e.g. through a TcpIp connection.

Saves an image to a JPEG file in the background thread.

Saves an image to a PNG file in the background thread.

Saves an image to a TIFF file in the background thread.

Captures an image from video file with using FFmpeg library.

Performs a morphological black top hat (bottom hat) operation on a image using an arbitrary kernel.

Removes small dark structures from an image (or fills in bright ones) by applying consecutive dilation and erosion.

E.g. removal of the "pepper" component of salt-and-pepper noise.

Removes small dark structures from an image (or fills in bright ones) by applying consecutive dilation and erosion.

E.g. removal of the "pepper" component of salt-and-pepper noise.

Applies difference of Gaussians on an image, i.e. computes difference of two Gaussian smoothed images.

Emphasizes high-frequency image features such as lines or patches / dots.

Replaces each pixel with the maximum of pixels within a kernel.

Thickens bright features in an images and thins dark ones.

Replaces each pixel with the maximum of pixels within a small rectangular kernel.

Replaces each pixel with the minimum of pixels within an arbitrary kernel.

Computes an image of gradient directions mapped to the range from 1 to 255. Zero means "no edge".

For highly optimized analysis of gradient directions.

Computes a gradient image with a Sobel or Prewitt operator.

Computes an image of gradient for only selected direction.

For highly optimized analysis of gradient directions.

Removes small bright structures from an image (or fills in dark ones) by applying consecutive erosion and dilation.

E.g. removal of the "salt" component of salt-and-pepper noise.

Smooths an image while preserving sharp edges.

Smooths the result of GradientDirAndPresenceImage.

Smooths an image using a predefined gaussian kernel.

Removal of gaussian noise from images (fast).

Smooths an image by averaging pixels within an arbitrary kernel.

Usually used for computing features related to local image "windows" having non-standard shape.

Replaces each pixel with the median of pixels within a kernel.

Edge-preserving noise removal (but slow).

Replaces each pixel with the average of maximum and minimum calculated within a kernel.

Useful for calculating per-pixel threshold values for image binarization.

Smooths an region by averaging pixels within a rectangular kernel.

Usually used for computing features related to local image "windows". Can be also used for noise removal, but Gauss is superior here.

Performs a morphological white top hat operation on a image using a predefined kernel.

Performs a morphological white top hat operation on a image using a predefined mask.

Compares each pixel with the specified color using chromatic and non-chromatic information.

Color analysis insensitive to changes of illumination.

Compares two pixels using CIE94 delta E. Assumes RGB color space.

Compares two images tile by tile using one of several available methods.

Computes the correlation of pattern and image.

Measures dissimilarity between two images.

Computes the average direction within the region of interest.

Computes the average of the HSV, HSL or HSI image pixel values.

Finds the location and the value of the darkest pixel.

Computes the sum of the image pixel values.

Adds random noise to the image.

Sets pixels below the low value to the low value and above the high value to the high value.

Divides each pixel by a scalar value.

Changes pixel values for data stored in array.

Reverts the pixel value range (unsigned) or applies numeric negation (signed).

Sets pixels below the low value to minimum, above the high value to maximum, and interpolates the rest.

Transforms pixels value from given range into new one.

Transforms pixel values to their square roots pixel by pixel.

Tests whether a box is contained in the dimensions of an image.

Tests whether a location is contained in the dimensions of a box.

Tests whether a point is contained in the dimensions of an image.

Creates affine transform matrix matrix. Return product of matrices: Translation * Rotation * Scale * Shearing.

Creates an array of images, each downsampled from the previous, gauss-smoothed one.

Frequently used to create scale-invariant image analysis algorithms. Reduces impact of pixel aliasing.

Creates an image from a quadrangle on another image.

Can be used for cropping an image from a slightly distorted rectangle. Do not use it for perspective distortion though.

Shrinks an image by the factor of two along each axis.

Usually used to speed-up image analysis at the cost of reduced precision. It is internally used to implement the pyramid strategy in template matching filters.

Creates an image from pixels traversed along an arc.

E.g. "Unwrapping" of object contours, so that they appear as 1D structures on the output image.

Transforms an image from polar or log-polar space to euclidean space.

Creates a single image by glueing together the two input images in horizontal or vertical direction.

Creates a single image by glueing together a series of input images in horizontal or vertical direction.

Joining images from a line-scan camera, which produces too few lines at a time.

Enlarges or shrinks an image to new dimensions.

Resizes an image by a factor along each axis.

Computes a leant image (shifts the rows).

Image preprocessing when there are slanted objects.

Transforms an image by the provided transformation matrix.

Moves the pixels of the input image by the vectors specified with inVectorImage.

Trims an image to the area of the specified region.

Returns individual fields of a spatial map.

Combines two spatial maps.

Makes it possible to use single RemapImage filter even if there are two or more image remapping operations (e.g. lens distortion + perspective distortion).

Converts a spatial map to a different format.

Converts any spatial map to NearestNeighbour interpolation.

Reducing quality for the purpose of speed.

Creates a spatial map representing an image inverse polar transform.

Data preprocessing for fast inverse polar transform. The result is used by RemapImage.

Creates a spatial map representing an image resizing.

Data preprocessing for fast image resize between two constant sizes. The result is used by RemapImage.

Creates a spatial map which performs transform defined as a 3x3 homography matrix.

Creates a perspective transform map from four points denoting a rectangle in the world coordinates.

Data preprocessing for fast perspective correction. The result is used by RemapImage.

Creates a spatial map for transformations from a sphere surface to a flat rectangle.

Inspection of the surface of balls and other spherical objects. The result is used by RemapImage.

Applies a precomputed image transform, defined by a spatial map object.

Fast (precomputed) image transformations, especially for view undistortion or object geometry correction (e.g. pos recognition of labels on cylindrical bottles).

Computes locations of image point on the source image from image point location on remapped image.

Transforms each pixel value to maximum or minimum depending on whether they belong to the specified range.

Image binarization when the illumination is constant and uniform.

Thresholds an image relatively to some value calculated in a local rectangular neighbourhood.

Image binarization when the illumination is uneven.

Thresholds an image with a hysteresis, i.e. with a lower threshold for neighboring pixels.

Thresholds an image with a different threshold value for each pixel (inBaseImage(x, y) + inValue).

Creates a region containing image pixels with values within the specified range.

Extraction of a region of objects that can be defined by a salient brightness.

Thresholds an image relatively to the average pixel value in a local rectangular neighborhood.

Useful in case of uneven illumination.

Thresholds an image with a different threshold value for each pixel (inBaseImage(x, y) + inValue).

Creates a region containing image pixels which belongs to the specified range for each individual pixel component.

Multi-channel thresholding.

Generates an array of boxes covering the area of an image.

Enumerates tiles from image.

Computes gradient magnitudes of an image.

Computes gradient orientations of an image.

Rotates image gradients.