Edge Texture Analysis for Image Retrieval Application with Aid of Robust Object Recognition
7 Published By: Blue Eyes Intelligence Engineering Sciences Publication Pvt. Ltd. Abstract It is a new approach in extension with local binary pattern and ternary pattern called DRLBP and DRLTP. By using these methods, the category recognition system will be developed for application to image retrieval. The category re cognition is to classify an object into one of several predefined c ategories. The discriminative robust local binary pattern (DRLBP) an d discriminative robust local ternary pattern (DRLTP) are used for different object texture and edge contour feature e xtraction process. It is robust to illumination and contrast variations as it only considers the signs of the pixel differences. The features retain the contrast information of image patterns. They contain both edge and texture information which is desirable for object recognition. The DRLBP discriminates an object like t he object surface texture and the object shape formed by its boundary. The boundary often shows much higher contrast between the object and the background than the surface texture. Differ entiating the boundary from the surface texture brings additional discriminatory information because the boundary con tains the shape information. These features are useful to dis tinguish the maximum number of samples accurately and it is matc hed with already stored image samples for similar category c lassification. The simulated results will be shown that used DRLBP and DRLTP has better discriminatory power and recognitio n accuracy compared with prior approaches.