Image Retrieval Implementation Using MATLAB

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Resource Overview

Image retrieval in MATLAB involves computing the distance (dis) between the query image and images in the database, then identifying the most similar image based on the minimum dis value, which indicates the same category as the query image.

Detailed Documentation

Image retrieval is a technique that identifies the most similar images from a database by computing the distance (dis) between the query image and each image in the database. In MATLAB, this process typically involves extracting image features (such as color histograms, texture patterns, or deep learning features) and calculating similarity metrics (like Euclidean distance, cosine similarity, or Hamming distance) to determine image similarity. The image with the smallest dis value belongs to the same category as the query image. This approach enables efficient retrieval of visually similar images from large databases. Key MATLAB functions for implementation may include pdist2 for distance calculations, imread for image loading, and feature extraction tools from the Computer Vision Toolbox.

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