Boosting local texture descriptors with Log-Gabor filters response for improved image retrieval

In the recent past, many local texture descriptors have been proposed for the image retrieval task. In order to improve the image retrieval accuracy, quite a few of these descriptors have been implemented on Gabor filter response. However, the response of Log-Gabor filters has been proved to be better than Gabor filters with respect to their discrimination ability. In this paper, we present a framework for image retrieval that applies various local texture descriptors on Log-Gabor filters response. To evaluate the retrieval performance of the proposed framework, experiments have been conducted on standard Wang, VisTex and OT-Scene databases. Consistent improvement in the image retrieval accuracy demonstrates the effectiveness of this framework. Further, the experimental results show that the use of proposed framework with low-dimension texture descriptors such as Orthogonal Combination of Local Binary Pattern makes them a better choice over Local Binary Pattern and its high-dimensional variants when higher retrieval accuracy, small feature vector size and ease of computation is desired.