Content Based Image Retrieval Using Uniform Local Binary Patterns

This paper proposes a simple yet effective method for image retrieval based on uniform local binary patterns. The proposed method is based on identification of several local binary patterns, called uniform local binary patterns. These are the essential properties of image texture and their histogram is verified to be a dominant texture feature. A generalized gray-scale and rotation invariant operator is constructed that identifies uniform patterns for each spatial resolution and for all quantization of the angular space. Color and shape features are also utilized in the calculation of feature vector. Additionally fourier descriptors (FD) and edge histogram descriptors (EHD) are computed to extort information at the edges thus increasing the performance of the system by giving higher precision. Euclidean distance is used as a similarity measure to find the distance between query and database image. Our proposed method demonstrates promising results for COREL image database compared to several recent CBIR systems.