Content based Image Retrieval based on Relevance Feedback and Collaborative Image Retrieval

SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 01, FEB 2018 PP.(252-256)

Abstract– Individual people are utilizing numerous handheld electronic gadgets like cell phones, cameras to take images of our everyday life. These images should have been put away in an expansive database. On the off chance that user needs specific picture to be recover from the database implies it will be to find those pictures and to recover it. So a proficient strategy for taking care of this issue is Content Based Image Retrieval (CBIR) System. The fundamental issue in CBIR is semantic gap and in light of this client can’t ready to get their pertinent picture. Because of this issue the performance of CBIR gets degraded. Inorder to enhance its performance the Relevance Feedback and Collaborative Image recovery strategy have been utilized. Relevance Feedback (RF) technique will reduce the semantic gap, just by asking relevance feedback about the image displayed to the user. In this article a relevant images have been recovered in light of Color and Texture by utilizing Global Color Histogram (GCH) and Local Binary Pattern (LBP) descriptor individually. To actualize Relevance criticism method, Supervised Learning has been utilized. Experiments are conducted in light of the proposed work and results are appeared.

Index Terms – Content Based Image Retrieval, Semantic gap, Relevance Feedback, Collaborative Image Retrieval, Global Color Histogram, Local Binary Pattern.

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N. Sathya, Dr. S. Rathi
Government College of Technology,
Coimbatore, India
sathyasivajan@gmail.com,
rathi@gct.ac.in

Content based Image Retrieval based on Relevance Feedback and Collaborative Image Retrieval

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