z-logo
open-access-imgOpen Access
Improvement in Performance of Image Retrieval using Various Features in CBIR System
Author(s) -
Dipesh Patel,
Darshan Patel
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016909005
Subject(s) - computer science , image retrieval , information retrieval , content based image retrieval , image (mathematics) , artificial intelligence
Content-Based image retrieval systems (CBIR) have become very popular for browsing, searching, and retrieving images from a large database of digital images as it requires relatively less human interference. In Content-based image retrieval system, visual feature. Color, texture and shape features have been the primitive image descriptors in CBIR systems. By using only color, texture or shape features, cannot get high precision. So, propose a new content-based image retrieval method that uses combination of color, shape and texture feature to get high precision. By using techniques like Image Processing, Data Mining, Machine Learning and Database for extracting color features, texture features and shape features, In this paper discuss the using various features and technique to possible get best precision as well as less computational complexity and good retrieval accuracy.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom