Color and Local Maximum Edge Patterns Histogram for Content Based Image Retrieval
K. Prasanthi Jasmine, P. Rajesh Kumar · International Journal of Intelligent Systems and Applications · 2014
In this paper, HSV color local maximum edge binary patterns (LM EBP) histogram and LM EBP joint histogram are integrated for content based image retrieval (CBIR).The local HSV region of image is represented by LM EBP, which are evaluated by taking into consideration the magnitude of local difference between the center pixel and its neighbors.This LM EBP differs from the existing LBP in a manner that it extracts the information based on distribution of edges in an image.Further the joint histogram is constructed between uniform two rotational invariant first three LM EBP patterns.The color feature is extracted by calculating the histogram on Hue (H), Saturation (S) and LM EBP histogram on Value (V) spaces.The feature vector of the system is constructed by integrating HSV LM EBP histograms and LM EBP joint histograms.The experimentation has been carried out for proving the worth of our algorithm.It is further mentioned that the databases considered for experiment are Corel-1K and Corel-5K.The results after being investigated show a significant improvement in terms of their evaluation measures as compared to previously available spatial and transform domain methods on their respective databases.