The OpenVX Specification  dba1aa3
Modules
Here is a list of all modules:
[detail level 1234]
 ▼Vision Functions These are the base vision functions supported in OpenVX 1.1 Absolute Difference Computes the absolute difference between two images. The output image dimensions should be the same as the dimensions of the input images Accumulate Accumulates an input image into output image. The accumulation image dimensions should be the same as the dimensions of the input image Accumulate Squared Accumulates a squared value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image Data Object Copy Copy a data object to another Accumulate Weighted Accumulates a weighted value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image Arithmetic Addition Performs addition between two images. The output image dimensions should be the same as the dimensions of the input images Arithmetic Subtraction Performs subtraction between two images. The output image dimensions should be the same as the dimensions of the input images Bitwise AND Performs a bitwise AND operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images Bitwise EXCLUSIVE OR Performs a bitwise EXCLUSIVE OR (XOR) operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images Bitwise INCLUSIVE OR Performs a bitwise INCLUSIVE OR operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images Bitwise NOT Performs a bitwise NOT operation on a VX_DF_IMAGE_U8 input image. The output image dimensions should be the same as the dimensions of the input image Box Filter Computes a Box filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image Non-Maxima Suppression Find local maxima in an image, or otherwise suppress pixels that are not local maxima Canny Edge Detector Provides a Canny edge detector kernel. The output image dimensions should be the same as the dimensions of the input image Channel Combine Implements the Channel Combine Kernel Channel Extract Implements the Channel Extraction Kernel Color Convert Implements the Color Conversion Kernel. The output image dimensions should be the same as the dimensions of the input image Convert Bit depth Converts image bit depth. The output image dimensions should be the same as the dimensions of the input image Custom Convolution Convolves the input with the client supplied convolution matrix. The output image dimensions should be the same as the dimensions of the input image Dilate Image Implements Dilation, which grows the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image Equalize Histogram Equalizes the histogram of a grayscale image. The output image dimensions should be the same as the dimensions of the input image Erode Image Implements Erosion, which shrinks the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image Fast Corners Computes the corners in an image using a method based upon FAST9 algorithm suggested in [3] and with some updates from [4] with modifications described below Gaussian Filter Computes a Gaussian filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image Non Linear Filter Computes a non-linear filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image Harris Corners Computes the Harris Corners of an image Histogram Generates a distribution from an image Gaussian Image Pyramid Computes a Gaussian Image Pyramid from an input image Laplacian Image Pyramid Computes a Laplacian Image Pyramid from an input image Reconstruction from a Laplacian Image Pyramid Reconstructs the original image from a Laplacian Image Pyramid Integral Image Computes the integral image of the input. The output image dimensions should be the same as the dimensions of the input image Magnitude Implements the Gradient Magnitude Computation Kernel. The output image dimensions should be the same as the dimensions of the input images Mean and Standard Deviation Computes the mean pixel value and the standard deviation of the pixels in the input image (which has a dimension width and height) Median Filter Computes a median pixel value over a window of the input image. The output image dimensions should be the same as the dimensions of the input image Min, Max Location Finds the minimum and maximum values in an image and a location for each Min Implements a pixel-wise minimum kernel. The output image dimensions should be the same as the dimensions of the input image Max Implements a pixel-wise maximum kernel. The output image dimensions should be the same as the dimensions of the input image Optical Flow Pyramid (LK) Computes the optical flow using the Lucas-Kanade method between two pyramid images Phase Implements the Gradient Phase Computation Kernel. The output image dimensions should be the same as the dimensions of the input images Pixel-wise Multiplication Performs element-wise multiplication between two images and a scalar value. The output image dimensions should be the same as the dimensions of the input images Remap Maps output pixels in an image from input pixels in an image Scale Image Implements the Image Resizing Kernel Sobel 3x3 Implements the Sobel Image Filter Kernel. The output images dimensions should be the same as the dimensions of the input image TableLookup Implements the Table Lookup Image Kernel. The output image dimensions should be the same as the dimensions of the input image Thresholding Thresholds an input image and produces an output Boolean image. The output image dimensions should be the same as the dimensions of the input image Warp Affine Performs an affine transform on an image Warp Perspective Performs a perspective transform on an image Bilateral Filter The function applies bilateral filtering to the input tensor MatchTemplate Compares an image template against overlapped image regions LBP Extracts LBP image from an input image. The output image dimensions should be the same as the dimensions of the input image HOG Extracts Histogram of Oriented Gradients features from the input grayscale image HoughLinesP Finds the Probabilistic Hough Lines detected in the input binary image Tensor Multiply Performs element wise multiplications on element values in the input tensor data with a scale Tensor Add Performs arithmetic addition on element values in the input tensor data Tensor Subtract Performs arithmetic subtraction on element values in the input tensor data Tensor TableLookUp Performs LUT on element values in the input tensor data Tensor Transpose Performs transpose on the input tensor Tensor Convert Bit-Depth Creates a bit-depth conversion node Tensor Matrix Multiply Creates a generalized matrix multiplication node Control Flow Defines the predicated execution model of OpenVX ▼Basic Features The basic parts of OpenVX needed for computation ▼Objects Defines the basic objects within OpenVX Object: Reference Defines the Reference Object interface Object: Context Defines the Context Object Interface Object: Graph Defines the Graph Object interface Object: Node Defines the Node Object interface Object: Array Defines the Array Object Interface Object: Convolution Defines the Image Convolution Object interface Object: Distribution Defines the Distribution Object Interface Object: Image Defines the Image Object interface Object: LUT Defines the Look-Up Table Interface Object: Matrix Defines the Matrix Object Interface Object: Pyramid Defines the Image Pyramid Object Interface Object: Remap Defines the Remap Object Interface Object: Scalar Defines the Scalar Object interface Object: Threshold Defines the Threshold Object Interface Object: ObjectArray An opaque array object that could be an array of any data-object (not data-type) of OpenVX except Delay and ObjectArray objects Object: Tensor Defines The Tensor Object Interface ▼Administrative Features Defines the Administrative Features of OpenVX ▼Advanced Objects Defines the Advanced Objects of OpenVX Object: Array (Advanced) Defines the advanced features of the Array Interface ▼Object: Node (Advanced) Defines the advanced features of the Node Interface Node: Border Modes Defines the border mode behaviors Object: Delay Defines the Delay Object interface Object: Kernel Defines the Kernel Object and Interface Object: Parameter Defines the Parameter Object interface ▼Advanced Framework API Describes components that are considered to be advanced Framework: Node Callbacks Allows Clients to receive a callback after a specific node has completed execution Framework: Performance Measurement Defines Performance measurement and reporting interfaces Framework: Log Defines the debug logging interface Framework: Hints Defines the Hints Interface Framework: Directives Defines the Directives Interface Framework: User Kernels Defines the User Kernels, which are a method to extend OpenVX with new vision functions Framework: Graph Parameters Defines the Graph Parameter API