Logarithmic distance measure with improved local vector pattern for content-based image retrieval

ABSTRACTThe development of image acquisition and data storage mechanisms have empowered the generation of broad image datasets. Under such circumstances, it is essential to promote the relevant information system to handle these collections properly. For this case, one of the most prominent methods is content-based image retrieval (CBIR) system, which can retrieve the required images from the large dataset. This paper proposes the CBIR system based on an informative pattern descriptor and a nonlinear similarity matching measure. The conventional retrieval process determines the distance between the feature library and the query features at the lower order and, subsequently, identifies the similar images with minimum distance. The proposed similarity measure will introduce the degree of similarity in logarithmic scale, and so the range of similar contents can be quantified. The experimental results affirm the beneficial part of PLVP method in providing a more informative and computationally efficient image...