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Rilevamento ed estrazione di feature

Registrazione di immagini, rilevamento del punto di interesse, estrazione dei descrittori delle feature, corrispondenza delle feature dei punti e recupero dell'immagine

Le feature locali e i loro descrittori sono i blocchi costitutivi di molti algoritmi di visione artificiale. Le loro applicazioni comprendono la registrazione di immagini, il rilevamento e la classificazione di oggetti, il tracking, la stima del movimento e il recupero dell'immagine sulla base del contenuto (CBIR). Questi algoritmi utilizzano feature locali per gestire meglio le variazioni di scala, la rotazione e l'occlusione. Gli algoritmi Computer Vision Toolbox™ comprendono i rilevatori di angoli FAST, Harris e Shi & Tomasi e i rilevatori di macchie SIFT, SURF, KAZE e MSER. La toolbox comprende i descrittori SIFT, SURF, FREAK, BRISK, LBP, ORB, e HOG. È possibile combinare i rilevatori e i descrittori in base ai requisiti dell'applicazione.

Funzioni

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Rilevamento delle feature

`detectBRISKFeatures`	Detect BRISK features
`detectFASTFeatures`	Detect corners using FAST algorithm
`detectHarrisFeatures`	Detect corners using Harris–Stephens algorithm
`detectKAZEFeatures`	Detect KAZE features
`detectMinEigenFeatures`	Detect corners using minimum eigenvalue algorithm
`detectMSERFeatures`	Detect MSER features
`detectORBFeatures`	Detect ORB keypoints
`detectSIFTFeatures`	Detect scale invariant feature transform (SIFT) features (Da R2021b)
`detectSURFFeatures`	Detect SURF features

Estrazione di feature

`extractFeatures`	Extract interest point descriptors
`extractLBPFeatures`	Extract local binary pattern (LBP) features
`extractHOGFeatures`	Extract histogram of oriented gradients (HOG) features

Corrispondenza delle feature

`matchFeatures`	Find matching features
`matchFeaturesInRadius`	Find matching features within specified radius (Da R2021a)

Acquisizione di immagini

`imwarp`	Apply geometric transformation to image
`estgeotform2d`	Estimate 2-D geometric transformation from matching point pairs (Da R2022b)
`estgeotform3d`	Estimate 3-D geometric transformation from matching point pairs (Da R2022b)
`vision.AlphaBlender`	(Not recommended) Combine images, overlay images, or highlight selected pixels
`vision.BlockMatcher`	Estimate motion between images or video frames
`vision.LocalMaximaFinder`	(Removed) Find local maxima in matrices
`vision.TemplateMatcher`	Locate template in image

Visualizzazione e display

`insertMarker`	Insert markers in image or video
`insertShape`	Insert shapes in image or video
`showMatchedFeatures`	Display corresponding feature points
`showShape`	Display shapes on image, video, or point cloud (Da R2020b)
`insertObjectAnnotation`	Annotate truecolor or grayscale image or video
`insertObjectKeypoints`	Insert object keypoints in image (Da R2023b)
`insertText`	Insert text in image or video
`imshow`	Display image
`imshowpair`	Compare differences between images
`vision.GammaCorrector`	(To be removed) Apply or remove gamma correction from images or video streams
`vision.ChromaResampler`	Downsample or upsample chrominance components of images

Archiviazione di feature

`binaryFeatures`	Object for storing binary feature vectors
`BRISKPoints`	Object for storing BRISK interest points
`cornerPoints`	Object for storing corner points
`KAZEPoints`	Object for storing KAZE interest points
`MSERRegions`	Object for storing MSER regions
`ORBPoints`	Object for storing ORB keypoints
`SIFTPoints`	Object for storing SIFT interest points (Da R2021b)
`SURFPoints`	Object for storing SURF interest points

Oggetti di trasformazione

`rigidtform2d`	2-D rigid geometric transformation (Da R2022b)
`simtform2d`	2-D similarity geometric transformation (Da R2022b)
`affinetform2d`	2-D affine geometric transformation (Da R2022b)
`projtform2d`	2-D projective geometric transformation (Da R2022b)
`rigidtform3d`	3-D rigid geometric transformation (Da R2022b)
`simtform3d`	3-D similarity geometric transformation (Da R2022b)

Acquisizione di immagini

Creazione di un database di riconoscimento

`bagOfFeatures`	Bag of visual words object
`invertedImageIndex`	Search index that maps visual words to images

Acquisizione di immagini

`retrieveImages`	Search image set for similar image
`imageDatastore`	Datastore for image data
`evaluateImageRetrieval`	Evaluate image search results

Argomenti

Local Feature Detection and Extraction
Learn the benefits and applications of local feature detection and extraction.
Point Feature Types
Choose functions that return and accept points objects for several types of features.
Sistemi di coordinate
Specificare gli indici dei pixel, le coordinate spaziali e i sistemi di coordinate in 3D
Draw Shapes and Lines
When you specify the type of shape to draw, you must also specify its location on the image.
Image Retrieval with Bag of Visual Words
Retrieve images from a collection of images similar to a query image using a content-based image retrieval (CBIR) system.

Esempi in primo piano

Image Retrieval Using Customized Bag of Features

Create a Content Based Image Retrieval (CBIR) system using a customized bag-of-features workflow.

Apri live script

Pattern Matching

Use the 2-D normalized cross-correlation for pattern matching and target tracking. The example uses predefined or user specified target and number of similar targets to be tracked. The normalized cross correlation plot shows that when the value exceeds the set threshold, the target is identified.

Apri script

Find Object in Cluttered Scene Using Image Point Features

Detect a particular object in a cluttered scene, given a reference image of the object.

Apri script

Digit Classification Using HOG Features

Classify digits using HOG features and a multiclass SVM classifier.

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Automatically Find Image Rotation and Scale

Demonstrates how to automatically determine the geometric transformation between two images. Specifically, when one image is distorted in relation to another due to rotation and scaling, the functions detectSURFFeatures and estimateGeometricTransform2D can be employed to identify the rotation angle and scale factor. Subsequently, these parameters can be used to transform the distorted image back to its original appearance.

Apri script

Create Panorama

Automatically stitch multiple images into panorama. The procedure for image stitching is an extension of feature based image registration. Instead of registering a single pair of images, multiple image pairs are successively registered relative to each other to form a panorama.

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Stabilize Video Using Image Point Features

Stabilize a video that was captured from a jittery platform. One way to stabilize a video is to track a salient feature in the image and use this as an anchor point to cancel out all perturbations relative to it. This procedure, however, must be bootstrapped with knowledge of where such a salient feature lies in the first video frame. In this example, we explore a method of video stabilization that works without any such a priori knowledge. It instead automatically searches for the "background plane" in a video sequence, and uses the observed distortion to correct for camera motion.

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Object Counting

Use morphological operations to count objects in a video stream.

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Cell Counting

Use a combination of basic morphological operators and blob analysis to extract information from a video stream. In this case, the example counts the number of E. Coli bacteria in each video frame. Note that the cells are of varying brightness, which makes the task of segmentation more challenging.

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