OpenCV Support

Convert camera parameters, MEX file support, and prebuilt MATLAB^® interfaces to OpenCV

The Computer Vision Toolbox™ Interface for OpenCV in MATLAB support package provides these functionalities for OpenCV support:

MATLAB functions to convert computed camera parameters between MATLAB and OpenCV formats for camera calibration applications.
OpenCV Interface C++ API support files for building MEX files that you can use to call OpenCV functions and integrate OpenCV C++ code into MATLAB. The support files contain graphics processing unit (GPU) support. You can use the MEX-based approach to integrate a custom OpenCV function with MATLAB. For more information about the MEX-based approach, see Build MEX-Files for OpenCV Interface.
Prebuilt MATLAB interface to the OpenCV library to directly call OpenCV functions from MATLAB without writing C/C++ code. The support package also provides MATLAB functions to pass data back and forth between OpenCV and MATLAB. However, the prebuilt MATLAB interface to the OpenCV does not provide support for integrating custom OpenCV functions with MATLAB.

To use the MEX-based and the prebuilt MATLAB interface to OpenCV support files, you must first download the Computer Vision Toolbox Interface for OpenCV in MATLAB support package. For information about how to download the support package, see Install and Use Computer Vision Toolbox Interface for OpenCV in MATLAB.

Functions

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Convert Camera Parameters

`cameraIntrinsicsFromOpenCV`	Convert camera intrinsic parameters from OpenCV to MATLAB
`cameraIntrinsicsToOpenCV`	Convert camera intrinsic parameters from MATLAB to OpenCV
`stereoParametersFromOpenCV`	Convert stereo camera parameters from OpenCV to MATLAB
`stereoParametersToOpenCV`	Convert stereo camera parameters from MATLAB to OpenCV

MEX Utility Functions for OpenCV Interface

OpenCV Interface C++ API

`ocvCheckFeaturePointsStruct`	Check that MATLAB struct represents feature points
`ocvStructToKeyPoints`	Convert MATLAB feature points struct to OpenCV `KeyPoint` vector
`ocvKeyPointsToStruct`	Convert OpenCV `KeyPoint` vector to MATLAB struct
`ocvMxArrayToCvRect`	Convert a MATLAB struct representing a rectangle to an OpenCV `CvRect`
`ocvCvRectToMxArray`	Convert OpenCV `CvRect` to a MATLAB struct
`ocvCvBox2DToMxArray`	Convert OpenCV `CvBox2D` to a MATLAB struct
`ocvCvRectToBoundingBox_{DataType}`	Convert `vector<cv::Rect>` to M-by-4 `mxArray` of bounding boxes
`ocvMxArrayToSize_{DataType}`	Convert 2-element `mxArray` to `cv::Size`.
`ocvMxArrayToImage_{DataType}`	Convert column major `mxArray` to row major `cv::Mat` for image
`ocvMxArrayToMat_{DataType}`	Convert column major `mxArray` to row major `cv::Mat` for generic matrix
`ocvMxArrayFromImage_{DataType}`	Convert row major `cv::Mat` to column major `mxArray` for image
`ocvMxArrayFromMat_{DataType}`	Convert row major `cv::Mat` to column major `mxArray` for generic matrix
`ocvMxArrayFromVector_{DataType}`	Convert numeric `vectorT` to `mxArray`
`ocvMxArrayFromPoints2f`	Converts `vector<cv::Point2f>` to `mxArray`

OpenCV Interface C++ API GPU

`ocvMxGpuArrayToGpuMat_{DataType}`	Create `cv::gpu::GpuMat` from `mxArray` containing GPU data.
`ocvMxGpuArrayFromGpuMat_{DataType}`	Create an `mxArray` from `cv::gpu::GpuMat` object

Prebuilt MATLAB Interface to OpenCV

`createMat`	Create MATLAB interface object for OpenCV `Mat` class
`createUMat`	Create MATLAB interface object for OpenCV `UMat` class
`getBasePtr`	Create MATLAB interface object for OpenCV base class
`getImage`	Read images stored in MATLAB interface object for OpenCV class
`keyPointsToStruct`	Convert OpenCV `KeyPoints` object to MATLAB structure
`rectToBbox`	Compute bounding boxes from outputs returned by MATLAB interface object for OpenCV `Rect` class

Support Package Installer

visionSupportPackages Start installer to download, install, or uninstall Computer Vision Toolbox data

Topics

Install and Use Computer Vision Toolbox Interface for OpenCV in MATLAB

Download and install support package for integrating OpenCV and MATLAB.

Build MEX-Files for OpenCV Interface

Create and test MEX- file based OpenCV interface.

Use Prebuilt MATLAB Interface to OpenCV

To call and execute OpenCV functions directly from MATLAB, use the prebuilt MATLAB interface.

Featured Examples

Perform Edge-Preserving Image Smoothing Using OpenCV in MATLAB

Perform edge-preserving image smoothing by using prebuilt MATLAB® interface to the OpenCV function cv::edgePreservingFilter. In this example, you also use the createMat utility function to define the input and output arrays, and the getImage utility function to read the output image returned by the OpenCV function.

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Subtract Image Background by Using OpenCV in MATLAB

Subtract the background in an image sequence or a video by using the prebuilt MATLAB interface to the OpenCV function cv::BackgroundSubtractorKNN. In this example, you also use the createMat utility function to define the input and output arrays, and the getImage utility function to read the output image returned by the OpenCV function. The input video must be have a static background and dynamic foreground objects.

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Perform Face Detection by Using OpenCV in MATLAB

Detect faces in an image or video by using prebuilt MATLAB® interface to the OpenCV function cv::CascadeClassifier. This example uses a Harr face detection model that is trained for scale-invariant, frontal face detection. In this example, you also use the createMat utility function to define the input and output arrays, the getImage utility function to read the output image returned by the OpenCV function, and the rectToBbox utility function to convert the face detection output returned by the OpenCV function to bounding box coordinates in MATLAB®.

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