Notice Board :

Call for Paper
Vol. 14 Issue 4

Submission Start Date:
May 01, 2022

Acceptence Notification Start:
May 10, 2022

Submission End:
May 20, 2022

Final MenuScript Due:
May 22, 2022

Publication Date:
May 25, 2021
                         Notice Board: Call for PaperVol. 14 Issue 4      Submission Start Date: May 01, 2022      Acceptence Notification Start: May 10, 2022      Submission End: May 20, 2022      Final MenuScript Due: May 22, 2022      Publication Date: May 25, 2021

Volume XII Issue XII

Author Name
Siddharth Kumar, Aman Saraf, Bhaskar Singh
Year Of Publication
Volume and Issue
Volume 12 Issue 12
In this paper Content-based image retrieval (CBIR) systems aim to return the most relevant images in a database, according to the user’s opinion for a given query. Due to the dynamic nature of the problem, which may change the meaning of relevance among users for a same query, these systems usually rely on an active learning process in which the system returns a small set of images (training set) and the user indicates their relevance at each iteration. Relevance feedback (RF) is an effective method for content-based image retrieval (CBIR), and it is also a feasible step to shorten the semantic gap between low-level visual feature and high-level Perception. increase in use of color image in recent years has motivated to the need of retrieval system for color image. Content Based Image Retrieval (CBIR) system is used to retrieve similar images from large image repositories based on color, texture and shape. In CBIR, the invariance to geometrical transformation is one of the most desire