Image Retrieval Techniques Using Content-Based Local Binary Descriptors

Abstract

In this chapter authors introduces content-based image retrieval systems and compares them over a common database. For this, four different content-based local binary descriptors are described with and without Gabor transform in brief. Further Nth derivative descriptor is calculated using (N-1)th derivative, based on rotational and multiscale feature extraction. At last the distance based query image matching is used to find the similarity with database. The performance in terms of average precision, average retrieval rate, different orders of derivatives in the form of average retrieval rate, and length of feature vector v/s performance in terms of time have been calculated. For this work a comparative experiment has been conducted using the Ponce Group images on seven classes (each class have 100 images). In addition, the performance of the all descriptors have been analyzed by combining these with the Gabor transform.