Computer Vision Toolbox with Simulink

Use Computer Vision Toolbox™ blocks to build models for computer vision applications. Perform feature detection, image analysis, FIR filtering, frequency and Hough transforms, morphology, contrast enhancement, and noise removal.

Local features and their descriptors are the building blocks of many computer vision algorithms. Their applications include image registration, object detection and classification, tracking, and motion estimation.

Motion estimation and tracking are key activities in applications including activity recognition, traffic monitoring, automotive safety, and surveillance.

Analysis and enhancement techniques enable you to increase the signal-to-noise ratio and accentuate features.

The showvipblockdatatypetable function provides details regarding block capabilities, limitations pertaining to code generation, variable-sizing, and supported data types for all Computer Vision Toolbox blocks.

Blocks

 Feature Detection and Recognition

Block	Description
Corner Detection	Calculate corner metric matrix and find corners in images
Edge Detection	Find edges of objects in images using Sobel, Prewitt, Roberts, or Canny method
Trace Boundary	Trace object boundaries in binary images
Template Matching	Locate a template in an image
Estimate Geometric Transformation	Estimate geometric transformation from matching point pairs
Find Local Maxima	Find local maxima in matrices
Template Matching	Locate a template in an image
Warp	Apply projective or affine transformation
Resize	Enlarge or shrink entire image or region of interest within image
Rotate	Rotate image by specified angle
Shear	Shift rows or columns of an image or a video frame by linearly varying offset
Translate	Translate image or video frame

 Object Detection

Block	Description
Deep Learning Object Detector	Detect objects using trained deep learning object detector

 Tracking and Motion Estimation

Block	Description
Block Matching	Estimate motion between images or video frames
Optical Flow	Estimate object velocities
Template Matching	Locate a template in an image

 Analysis and Statistics

Block	Description
2-D Autocorrelation	2-D autocorrelation of input matrix
2-D Correlation	Compute 2-D correlation of two input matrices
2-D Histogram	Generate histogram from input
2-D Maximum	Compute maximum value of input or sequence of inputs
2-D Mean	Find 2-D mean of input array
2-D Median	2-D Median values of input array
2-D Minimum	Find minimum values in input or sequence of inputs
2-D Standard Deviation	Compute standard deviation of input or sequence of inputs
2-D Variance	Compute variance of input or sequence of inputs
Blob Analysis	Statistics for labeled regions
Find Local Maxima	Find local maxima in matrices
PSNR	Compute peak signal-to-noise ratio (PSNR) between images

 Morphological Operations

Block	Description
Morphological Operations
Bottom-hat	Perform morphological bottom-hat filtering on intensity or binary images
Closing	Perform morphological closing on binary or intensity images
Dilation	Dilate binary or intensity image by finding local maxima
Erosion	Find local minima in binary or intensity image
Label	Label connected components in binary image
Opening	Perform morphological opening on binary or intensity images
Top-hat	Perform morphological top-hat filtering on intensity or binary images

 Filters, Transforms, and Enhancements

Block	Description
2-D Convolution	Compute 2-D discrete convolution of two input matrices
2-D FFT	Compute 2-D fast Fourier transform (FFT)
2-D IFFT	Compute 2-D inverse fast Fourier transform (IFFT)
2-D DCT	Compute 2-D discrete cosine transform (DCT)
2-D IDCT	Compute 2-D inverse discrete cosine transform (IDCT)
2-D FIR Filter	2-D FIR filter on input matrix
Block Matching	Estimate motion between images or video frames
Block Processing	Repeat user-specified operation on blocks of input matrix
Contrast Adjustment	Adjust image contrast using linear scaling
Deinterlacing	Remove interlacing effect
Edge Detection	Find edges of objects in images using Sobel, Prewitt, Roberts, or Canny method
Histogram Equalization	Enhance contrast of images using histogram equalization
Median Filter	Perform 2-D median filtering
Hough Transform	Find lines in images
Hough Lines	Find Cartesian coordinates of lines described by rho and theta pairs
Gaussian Pyramid	Perform Gaussian pyramid decomposition

 Video Loading, Saving, and Display

Block	Description
Video Loading, Saving, and Display
Write Binary File	Write binary video data to file
Image From File	Read image from file location
Image From Workspace	Import image from MATLAB workspace
Video Viewer	Display images or video frames
From Multimedia File	Read video frames and audio samples from multimedia file
To Multimedia File	Write video frames and audio samples to multimedia file
To Video Display	Display images or video frames
Frame Rate Display	Calculate and display video frame rate
Video To Workspace	Export image or video to MATLAB workspace
Video From Workspace	Import video from MATLAB workspace
Read Binary File	Read video data from binary file

 Graphics

Block	Description
Compositing	Combine two images or apply mask to image
Draw Markers	Draw markers on image
Draw Shapes	Draw rectangles, lines, polygons, or circles on images
Image Pad	Pad image by adding rows, columns, or both
Insert Text	Draw text on images or video frames

 Visualize Point Clouds

Block	Description
Point Cloud Viewer	Visualize streaming point cloud data sequence

 Simulink Image Type

Object	Description
Simulink.ImageType	Specify image data type

Examples

Read and Write Video

• Read, Process, and Write Video Frames to File

• Read Video Stored as Binary Data

• Write Image to Binary File

Annotate and Display Data

• Read and Display RGB Video from File

• Read, Convert, and View Video from File

• Draw Rectangles on Image

• Draw Markers on Image

• Insert Text into Image

• Visualize Point Cloud Sequence

Applications

• Pattern Matching

• Object Counting

• Video Stabilization

• Barcode Recognition Using Live Video Acquisition

• Edge Detection Using Live Video Acquisition

• Detect and Track Face

• Develop Visual SLAM Algorithm Using Unreal Engine Simulation

• Stereo Visual SLAM for UAV Navigation in 3D Simulation

• Deep Learning Vehicle Detector from IP Camera Stream on Jetson (GPU Coder)

• Deploy and Verify YOLO v2 Vehicle Detector on FPGA (Vision HDL Toolbox)

• Lane and Vehicle Detection in Simulink Using Deep Learning (Deep Learning Toolbox)