International Journal of Managment, IT and Engineering
  • Year: 2013
  • Volume: 3
  • Issue: 3

Analysis for image retrieval of texture, color and shape features

  • Author:
  • Amanbir Sandhu, Aarti Kochhar
  • Total Page Count: 9
  • Page Number: 386 to 394

*Lecturer, Rayat Bahra College of Engineering & Nanotechnology For Women, Hoshiarpur

**Assistant Professor, Dav Institute of Engineering & Technology, Jalandhar

Online published on 24 October, 2013.

Abstract

Content- Based Image Retrieval(CBI is the important field of research.Content Based Image retrieval has gained much popularity in the past Content-based image retrieval (CBIR)[1] system has helped users to retrieve relevant images based on their contents. It represents low level features like texture, color and shape. In this paper, we compare the several feature extraction techniques [5]i.e..GLCM, Histogram and shape properties over color, texture and shape The experiments show the similarity between these features and also that the output obtained using this combination of color, texture and shape is better as obtaining output with a single feature.

Keywords

Gray Level Cooccurence Matrix(GLCM), Histogram, Shape features, Precision, Recall, Accuracy