Context Re-Ranking in Sketch Based Image Retrieval
Durga Prasad Kalasapati1, Manjunathachari Kamsali2, Giri Prasad Mahendra Nanjappa3
1Durga Prasad Kalasapati, Department of ECE, JNTUA, Ananthapuramu, (A.P), India.
2Manjunathachari Kamsali, Department of ECE,GITAM University Hyderabad, (Telangana), India.
3Giri Prasad Mahendra Nanjappa, Department of ECE, JNTUA, Ananthapuramu, (A.P), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 362-369 | Volume-7 Issue-6, March 2019 | Retrieval Number: E2082017519©BEIESP
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© 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: Image retrieval based on the sketch-based descriptor is focused in this paper. The retrieval operation based on the sha pe details defined in a sketch input is used for image region descriptor and a distance based mapping approach is developed for image retrieval in a database system. The search overhead, decision accuracy and feature representation is constraint to such sketch based approach, hence in this paper, a context re-ranking model based on feedback modeling is proposed. The approach has an advantage of faster retrieval performance compared to the conventional retrieval system. The validation is made with the simulation result developed for the proposed approach over the conventional benchmark approach.
Keywords: Sketch based image retrieval, context feature, re-ranking, feedback modeling
Scope of the Article: Image Security