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Computer Vision with Simulink

Simulink® support for computer vision applications

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.


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Corner DetectionCalculate corner metric matrix and find corners in images
Edge DetectionFind edges of objects in images using Sobel, Prewitt, Roberts, or Canny method
Trace BoundaryTrace object boundaries in binary images
Template MatchingLocate a template in an image
Estimate Geometric TransformationEstimate geometric transformation from matching point pairs
Find Local MaximaFind local maxima in matrices
Template MatchingLocate a template in an image
WarpApply projective or affine transformation
ResizeEnlarge or shrink entire image or region of interest within image
RotateRotate image by specified angle
ShearShift rows or columns of an image or a video frame by linearly varying offset
TranslateTranslate image in 2-D plane using displacement vector
Deep Learning Object DetectorDetect objects using trained deep learning object detector (Seit R2021b)
Block MatchingEstimate motion between images or video frames
Optical FlowEstimate object velocities
Template MatchingLocate a template in an image
2-D Autocorrelation 2-D autocorrelation of input matrix
2-D CorrelationCompute 2-D correlation of two input matrices
2-D HistogramGenerate histogram from input
2-D MaximumCompute maximum value of input or sequence of inputs
2-D MeanFind 2-D mean of input array
2-D Median 2-D Median values of input array
2-D MinimumFind minimum values in input or sequence of inputs
2-D Standard DeviationCompute standard deviation of input or sequence of inputs
2-D VarianceCompute variance of input or sequence of inputs
Blob AnalysisStatistics for labeled regions
Find Local MaximaFind local maxima in matrices
PSNRCompute peak signal-to-noise ratio (PSNR) between images
Bottom-hatPerform morphological bottom-hat filtering on intensity or binary images
ClosingPerform morphological closing on binary or intensity images
DilationDilate binary or intensity image by finding local maxima
ErosionFind local minima in binary or intensity image
LabelLabel connected components in binary image
OpeningPerform morphological opening on binary or intensity images
Top-hatPerform morphological top-hat filtering on intensity or binary images
AutothresholdConvert intensity image to binary image
Chroma ResamplingDownsample or upsample chrominance components of images
Color Space ConversionConvert color space of image
DemosaicDemosaic Bayer format images
Gamma CorrectionApply or remove gamma correction to or from image or video stream
Image ComplementCompute the complement of pixel values in binary or intensity images
Image Data Type ConversionConvert and scale input image to specified output data type
Image PadPad image by adding rows, columns, or both
To Simulink ImagePack numeric matrix into a Simulink image (Seit R2022a)
From Simulink ImageUnpack numeric matrix from Simulink image (Seit R2022a)
Image AttributesOutput attributes of Simulink image signal (Seit R2022b)
2-D ConvolutionCompute 2-D discrete convolution of two input matrices
2-D FFTCompute 2-D fast Fourier transform (FFT)
2-D IFFTCompute 2-D inverse fast Fourier transform (IFFT)
2-D DCTCompute 2-D discrete cosine transform (DCT)
2-D IDCTCompute 2-D inverse discrete cosine transform (IDCT)
2-D FIR Filter2-D FIR filter on input matrix
Block MatchingEstimate motion between images or video frames
Block ProcessingRepeat user-specified operation on blocks of input matrix
Contrast AdjustmentAdjust image contrast using linear scaling
DeinterlacingRemove interlacing effect
Edge DetectionFind edges of objects in images using Sobel, Prewitt, Roberts, or Canny method
Histogram EqualizationEnhance contrast of images using histogram equalization
Median FilterPerform 2-D median filtering
Hough TransformFind lines in images
Hough LinesFind Cartesian coordinates of lines described by rho and theta pairs
Gaussian PyramidPerform Gaussian pyramid decomposition
Write Binary FileWrite binary video data to file
Image From FileRead image from file location
Image From WorkspaceImport image from MATLAB workspace
Video ViewerDisplay images or video frames
From Multimedia FileRead video frames and audio samples from multimedia file
To Multimedia FileWrite video frames and audio samples to multimedia file
To Video DisplayDisplay images or video frames
Frame Rate DisplayCalculate and display video frame rate
Video To WorkspaceExport image or video to MATLAB workspace
Video From WorkspaceImport video from MATLAB workspace
Read Binary File Read video data from binary file
CompositingCombine two images or apply mask to image
Draw MarkersDraw markers on image
Draw ShapesDraw rectangles, lines, polygons, or circles on images
Image PadPad image by adding rows, columns, or both
Insert TextDraw text on images or video frames
Point Cloud ViewerVisualize streaming point cloud data sequence (Seit R2023a)


Simulink.ImageTypeSpecify image data type (Seit R2021b)


  • Video Formats

    Video data is a series of images over time.

  • Image Formats

    In the Computer Vision Toolbox software, images are real-valued ordered sets of color or intensity data.

  • Fixed-Point Signal Processing

    Discusses advantages of fixed-point development in general and of fixed-point support in System Toolbox software in particular, as well as lists common applications of fixed-point signal processing development.

  • Fixed-Point Concepts and Terminology

    Defines fixed-point concepts and terminology that are helpful to know as you use DSP System Toolbox™ software.

  • Arithmetic Operations

    Describes the arithmetic operations used by fixed-point DSP System Toolbox blocks, including operations and casts that might invoke rounding and overflow handling methods.

  • Fixed-Point Support for MATLAB System Objects

    Fixed-Point support for Computer Vision Toolbox System Objects

  • Specify Fixed-Point Attributes for Blocks (DSP System Toolbox)

    Teaches you how to specify fixed-point attributes and parameters in software on both the block and system levels.

  • Visualize Point Cloud Sequence

    This example shows how to visualize a streaming point cloud sequence by using a Point Cloud Viewer block.