Main Content

Feature Detection and Extraction

Image registration, interest point detection, feature descriptor extraction, point feature matching, and image retrieval

Local features and their descriptors are the building blocks of many computer vision algorithms. Their applications include image registration, object detection and classification, tracking, motion estimation, and content-based image retrieval (CBIR). These algorithms use local features to better handle scale changes, rotation, and occlusion. Computer Vision Toolbox™ algorithms include the FAST, Harris, and Shi & Tomasi corner detectors, and the SIFT, SURF, KAZE, and MSER blob detectors. The toolbox includes the SIFT, SURF, FREAK, BRISK, LBP, ORB, and HOG descriptors. You can mix and match the detectors and the descriptors depending on the requirements of your application.

Funzioni

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detectBRISKFeaturesDetect BRISK features
detectFASTFeaturesDetect corners using FAST algorithm
detectHarrisFeaturesDetect corners using Harris–Stephens algorithm
detectKAZEFeaturesDetect KAZE features
detectMinEigenFeaturesDetect corners using minimum eigenvalue algorithm
detectMSERFeaturesDetect MSER features
detectORBFeaturesDetect ORB keypoints
detectSIFTFeaturesDetect scale invariant feature transform (SIFT) features (Da R2021b)
detectSURFFeaturesDetect SURF features
extractFeaturesExtract interest point descriptors
extractLBPFeaturesExtract local binary pattern (LBP) features
extractHOGFeaturesExtract histogram of oriented gradients (HOG) features
matchFeaturesFind matching features
matchFeaturesInRadiusFind matching features within specified radius (Da R2021a)
imwarpApply geometric transformation to image
estgeotform2dEstimate 2-D geometric transformation from matching point pairs (Da R2022b)
estgeotform3dEstimate 3-D geometric transformation from matching point pairs (Da R2022b)
vision.AlphaBlenderCombine images, overlay images, or highlight selected pixels
vision.BlockMatcherEstimate motion between images or video frames
vision.LocalMaximaFinder(To be removed) Find local maxima in matrices
vision.TemplateMatcherLocate template in image
insertMarkerInsert markers in image or video
insertShapeInsert shapes in image or video
showMatchedFeaturesDisplay corresponding feature points
showShapeDisplay shapes on image, video, or point cloud (Da R2020b)
insertObjectAnnotationAnnotate truecolor or grayscale image or video
insertObjectKeypointsInsert object keypoints in image (Da R2023b)
insertTextInsert text in image or video
imshowDisplay image
imshowpairCompare differences between images
vision.GammaCorrector(To be removed) Apply or remove gamma correction from images or video streams
vision.ChromaResamplerDownsample or upsample chrominance components of images
binaryFeaturesObject for storing binary feature vectors
BRISKPointsObject for storing BRISK interest points
cornerPointsObject for storing corner points
KAZEPointsObject for storing KAZE interest points
MSERRegionsObject for storing MSER regions
ORBPointsObject for storing ORB keypoints
SIFTPointsObject for storing SIFT interest points (Da R2021b)
SURFPointsObject for storing SURF interest points
rigidtform2d2-D rigid geometric transformation (Da R2022b)
simtform2d2-D similarity geometric transformation (Da R2022b)
affinetform2d2-D affine geometric transformation (Da R2022b)
projtform2d2-D projective geometric transformation (Da R2022b)
rigidtform3d3-D rigid geometric transformation (Da R2022b)
simtform3d3-D similarity geometric transformation (Da R2022b)

Create Recognition Database

bagOfFeaturesBag of visual words object
invertedImageIndexSearch index that maps visual words to images

Retrieve Images

retrieveImagesSearch image set for similar image
imageDatastoreDatastore for image data
evaluateImageRetrievalEvaluate image search results

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