LSH high dimension index algorithm based on thumbnails

Jinjin Zhu; Yaping Cai

doi:10.1117/12.2580693

10 November 2020 LSH high dimension index algorithm based on thumbnails

Jinjin Zhu, Yaping Cai

Proceedings Volume 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence; 115840Q (2020) https://doi.org/10.1117/12.2580693
Event: Third International Conference on Image, Video Processing and Artificial Intelligence, 2020, Shanghai, China

Abstract

Aiming at the hierarchical index method of large image features, the hierarchical index structure of large image is established by using the global position constraint information of large image. This method combines LSH algorithm and KD tree algorithm based on location information. It can control the space complexity of LSH algorithm and the time complexity of KD tree algorithm in high-dimensional feature retrieval. It can speed up the search speed and improve the accuracy of finding the nearest neighbor features, so as to obtain the best comprehensive search performance compared with LSH algorithm and KD tree algorithm. This method mainly includes: extracting thumbnail to build two-layer pyramid image index structure, using LSH algorithm to search rough location for thumbnail, and using KD tree algorithm based on location information to search feature points near neighbor for original image.

Citation Download Citation

Jinjin Zhu and Yaping Cai "LSH high dimension index algorithm based on thumbnails", Proc. SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence, 115840Q (10 November 2020); https://doi.org/10.1117/12.2580693

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KEYWORDS

Feature extraction

Image retrieval

Binary data

Image processing

Communication engineering

Content based image retrieval

Environmental sensing

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