A fast descriptor matching algorithm for exhaustive search in large databases

Abstract

In order to find the best match to a query image in a database, conventional content-based image retrieval schemes need the exhaustive search, where the descriptor of the query, e.g., histogram, must be compared with literally all images in the database. However, the straightforward exhaustive search algorithm is computationally expensive. So, fast exhaustive search algorithms are demanded. This paper presents a fast exhaustive search algorithm based on a multi-resolution descriptor structure and a norm-sorted database. First, we derive a condition to eliminate unnecessary matching operations from the search procedure by using a norm-sorted structure of the database. Then, we propose a fast search algorithm based on the elimination condition, which guarantees an exhaustive search for either the best match or multiple best matches to a query. With a luminance histogram as a descriptor, we show that the proposed algorithm provides a search accuracy of 100% with high search speed.