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.

Apps

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

Functions

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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

Topics

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

Image Retrieval Using Customized Bag of Features

Image Retrieval Using Customized Bag of Features

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

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Image Category Classification Using Bag of Features

Image Category Classification Using Bag of Features

Use a bag of features approach for image category classification. This technique is also often referred to as bag of words. Visual image categorization is a process of assigning a category label to an image under test. Categories may contain images representing just about anything, for example, dogs, cats, trains, boats.

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Image Category Classification Using Deep Learning

Image Category Classification Using Deep Learning

Use a pretrained Convolutional Neural Network (CNN) as a feature extractor for training an image category classifier.

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Computer Vision Toolbox Documentation

Support