Open AccessA Review on LBP in Image Retrieval System for Future Enhancement and Vector Images
Author(s) -
K. Rajalakshmi,
V Krishna Dharshini,
Sachin Meena
Publication year - 2020
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-666
Subject(s) - image retrieval , computer science , artificial intelligence , content based image retrieval , image texture , computer vision , pattern recognition (psychology) , visual word , pixel , similarity (geometry) , image (mathematics) , matching (statistics) , automatic image annotation , process (computing) , feature extraction , feature (linguistics) , set (abstract data type) , feature detection (computer vision) , image processing , mathematics , statistics , programming language , operating system , linguistics , philosophy
Content-Based Image Retrieval is a process to retrieve the similar images from the large set of image database corresponding to the query image. In CBIR low level or pixel level features such as color, texture and shape of the images are extracted and on the basis of similarity matching algorithm the required similar kind of images are retrieved from the image database. To understand the evaluation and evolution of CBIR system various research was studied and various research is going on this way also. In this paper, we have discussed some of the popular pixel level feature extraction techniques for Content-Based Image Retrieval and we also present here about the performance of each technique.