ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

Retrieval Techniques for Feature Extraction in CBIR System

Journal: International Journal of Science and Research (IJSR) (Vol.8, No. 4)

Publication Date:

Authors : ; ;

Page : 65-68

Keywords : CBIR; Similarity Matrix; DWT; SVM; GLCM; Global feature; Local feature; Color Correlogram; Color Histogram;

Source : Downloadexternal Find it from : Google Scholarexternal

Abstract

CBIR (Content-Based Image Retrieval) uses the visual contents of a picture like global features-color feature, shape feature, texture feature, and local features-spatial domain present to signify and index the image. CBIR method combines global and local features. In this paper worked on Hear Discrete Wavelet Transform (HDWT) for decaying an image into horizontal, vertical and diagonal region and Gray Level Coo-ccurrence Matrix (GLCM) for feature extraction. In this paper for classification process, Support Vector Machine (SVM) used. The experimental results show improved results in comparison to previous methods. In this paper, proposed a calculation which consolidates the advantages of a few different calculations to improve the exactness and execution of recovery.

Last modified: 2021-06-28 18:10:01