A Novel Methodology for Efficient Retrievals of Sketch Based Images using Local Binary Patterns and Generalized Gamma Mixture Models (GGMM)
K M Vara Prasad1, Ande Prasad2

1K M Vara Prasad, Research Scholar, Department of Computer Science, Vikrama Simhapuri University, Nellore.
2Ande Prasad, Professor, Department of Computer Science, Vikrama Simhapuri University, Nellore.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 5-9 | Volume-6 Issue-7, January 2020. | Retrieval Number: 100.1/ijese.G2331016720 | DOI: 10.35940/ijese.G2331.016720
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© The Authors. Published By: 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: The enormous work in Information technology sector met towards the development of methodologies for identifying or retrieving the images based on content. However in specific conditions narration is the best suitable way to express and hence basing the views of narration sketch based images are thus developed and utilized. These sketch based images are most useful in criminal investigations. The present article portrays a methodology for retrieving such sketch based images using the statistical modeling approaches.
Keywords: Statistical models, criminal applications, Sketch-based Images, experimental evaluation, content based retrievals.