PixSearcher: Searching similar images in large image collections through pixel descriptors

Tuan Nhon Dang, Leland Wilkinson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Searching and mining huge image databases has become a daunting task for many application areas such as astronomy, medicine, geology, oceanography, and crime prevention. We introduce a new image indexing and retrieval system, PixSearcher, that computes image descriptors from pixels obtained by thresholding images at different levels. In contrast to raster techniques (which use the entire pixel raster for distance computations), PixSearcher uses a small set of descriptors and consequently can handle large image collections within reasonable time. We use benchmark image databases from different domains to evaluate PixSearcher’s performance versus well-known image retrieval techniques.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
EditorsGeorge Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Kambhamettu Chandra, El Choubassi Maha, Zhigang Deng, Mark Carlson
Number of pages10
ISBN (Electronic)9783319143637
StatePublished - 2014
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: Dec 8 2014Dec 10 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Symposium on Visual Computing, ISVC 2014
Country/TerritoryUnited States
CityLas Vegas


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