Retrieval of Context and Content based Images using Enhanced Crow Search Optimization
T.Y.Srinivasa Rao1, P.Chenna Reddy2
1T.Y.Srinivasa Rao*, Research Scholar, CSE Department, JNTUK, Kakinada, India.
2Dr. P. Chenna Reddy, CSE Department, JNTU, Ananthapur, India.
Manuscript received on August 03, 2019. | Revised Manuscript received on August 30, 2019. | Manuscript published on August 30, 2019. | PP: 2990-2995 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9009088619/2019©BEIESP | DOI: 10.35940/ijeat.F9009.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In late decades, Content-Based Image Retrieval (CBIR) has been one on the most distinctive research zones in the field of Computer applications. The critical goal of this examination is to improve the recovering presentation of CBIR framework by fusing advancement strategies to foresee suitable centroid in Fuzzy C-Means (FCM).The expectation of consolidating streamlining method to anticipate FCM centroids positively decrease intricacy and computational time. The outcomes clear that consolidation of ECSO with FCM uncovers better outcomes over challenge procedures when compared with existing procedures like PWO, SSO and CSO.
Keywords: Crow Search Optimization, PWO, SSO, CSO, FCM.