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使用 Simulink 实现计算机视觉
R2025b使用 Computer Vision Toolbox™ 模块为计算机视觉应用构建模型。执行特征检测、图像分析、FIR 滤波、频率和霍夫变换、形态学运算、对比度增强和去噪。
局部特征及其描述符是许多计算机视觉算法的构建块。其应用包括图像配准、目标检测和分类、跟踪和运动估计。
运动估计和跟踪是活动识别、交通监控、汽车安全和监督等应用中的关键活动。
分析和增强方法使您能够提高信噪比和突出特征。
showvipblockdatatypetable 函数提供有关所有 Computer Vision Toolbox 模块的模块功能、代码生成限制、可变大小和支持的数据类型的详细信息。
模块
 | 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 |
 | Deep Learning Object Detector | 使用经过训练的深度学习目标检测器检测目标 |
 | Block Matching | Estimate motion between images or video frames |
 | Optical Flow | Estimate object velocities |
| Template Matching | Locate a template in an image |
 | 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 |
 | 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 |
 | Autothreshold | Convert intensity image to binary image |
 | Chroma Resampling | Downsample or upsample chrominance components of images |
 | Color Space Conversion | Convert color space of image |
 | Demosaic | Demosaic Bayer format images |
 | Gamma Correction | Apply or remove gamma correction to or from image or video stream |
 | Image Complement | Compute the complement of pixel values in binary or intensity images |
 | Image Data Type Conversion | Convert and scale input image to specified output data type |
 | Image Pad | Pad image by adding rows, columns, or both |
 | To Simulink Image | Pack numeric matrix into a Simulink image (自 R2022a 起) |
 | From Simulink Image | Unpack numeric matrix from Simulink image (自 R2022a 起) |
 | Image Attributes | Output attributes of Simulink image signal (自 R2022b 起) |
 | 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 |
 | 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 |
 | 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 |
| Point Cloud Viewer |
对象
Simulink.ImageType | Specify image data type |
主题
- 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.
- 对 MATLAB System object 的定点支持
对 Computer Vision Toolbox System object 启用定点支持。
- 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.
精选示例
Track Marker Using Simulink Images
Track a marker on a whiteboard by using images of the Simulink.ImageType data type.
Pattern Matching
Use the 2-D normalized cross-correlation for pattern matching and target tracking.
Object Counting
Use basic morphological operators to extract information from a video stream. In this case, the model counts the number of staples in each video frame. Note that the focus and lighting change in each video frame.
Video Stabilization
Remove the effect of camera motion from a video stream.
Barcode Recognition Using Live Video Acquisition
Use the From Video Device block provided by Image Acquisition Toolbox™ to acquire live image data from a Point Grey Flea® 2 camera into Simulink®. The example uses the Computer Vision Toolbox™ to create an image processing system which can recognize and interpret a GTIN-13 barcode. The GTIN-13 barcode, formally known as EAN-13, is an international barcode standard. It is a superset of the widely used UPC standard.
Edge Detection Using Live Video Acquisition
Use the From Video Device block provided by Image Acquisition Toolbox™ to acquire live image data from a Hamamatsu C8484 camera into Simulink®. The Prewitt method is applied to find the edges of objects in the input video stream.
