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Image Category Classification and Image Retrieval

Create a bag of visual words for image classification and content-based image retrieval (CBIR) systems

To classify images into categories, you generate a histogram of visual word occurrences that represent an image. These histograms, called a bag of visual words, are used to train an image category classifier. You can also use the Computer Vision Toolbox™ functions to search by image, also known as a content-based image retrieval (CBIR) system. CBIR systems are used to retrieve images from a collection of images that are similar to a query image.


Image LabelerLabel images for computer vision applications
Video LabelerLabel video for computer vision applications


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trainImageCategoryClassifierTrain an image category classifier
bagOfFeaturesBag of visual words object
imageCategoryClassifierPredict image category
invertedImageIndexSearch index that maps visual words to images
evaluateImageRetrievalEvaluate image search results
indexImagesCreate image search index
retrieveImagesSearch image set for similar image
imageDatastoreDatastore for image data


Get Started

Get Started with the Image Labeler

Interactively label rectangular ROIs for object detection, pixels for semantic segmentation, and scenes for image classification.

Classify Images

Create a Custom Feature Extractor

You can use the bag-of-features (BoF) framework with many different types of image features.

Image Classification with Bag of Visual Words

Use the Computer Vision Toolbox functions for image category classification by creating a bag of visual words.

Featured Examples