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. Using local features enables these algorithms to better handle scale changes, rotation, and occlusion. The Computer Vision System Toolbox™ provides the FAST, Harris, and Shi & Tomasi corner detectors, and the SURF and MSER blob detectors. The toolbox includes the SURF, FREAK, BRISK, and HOG descriptors. The detectors and the descriptors can be mixed and matched depending on the requirements of your application.
|detectBRISKFeatures||Detect BRISK features and return BRISKPoints object|
|detectFASTFeatures||Detect corners using FAST algorithm and return cornerPoints object|
|detectHarrisFeatures||Detect corners using Harris–Stephens algorithm and return cornerPoints object|
|detectMinEigenFeatures||Detect corners using minimum eigenvalue algorithm and return cornerPoints object|
|detectMSERFeatures||Detect MSER features and return MSERRegions object|
|detectSURFFeatures||Detect SURF features and return SURFPoints object|