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.
CITATION STYLE
Dang, T. N., & Wilkinson, L. (2014). PixSearcher: Searching similar images in large image collections through pixel descriptors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8888, pp. 726–735). Springer Verlag. https://doi.org/10.1007/978-3-319-14364-4_70
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