Author(s): Sambu Patach Arrojula
Image similarity searching is a well-explored topic with numerous techniques and approaches, each offering unique advantages. In this paper, we present an approach aimed at accelerating the search for the most similar images to a given query image within an image database. Our method leverages the principles of Locality-Sensitive Hashing (LSH) but relies on a concept of similarity boundaries to reach the search to most appropriate section and in turn facilitates a rapid retrieval of most similar content.We assume the availability of a reliable hash function for image similarity that offers high accuracy and a low collision rate and focus exclusively on the algorithm designed to maintain and manage similarity boundaries for each image within the hashtable. This strategic organization ensures that similar images are grouped together logically, significantly enhancing the efficiency and speed of the search process.
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