A Methodology for Efficient Sketch Based Image Retrievals Based on Correlation Based Matching and Generalized Gamma Mixture Model (GGMM)
K M Vara Prasad1, Ande Prasad2
1K M Vara Prasad*, Research Scholar, Department of Computer Science, Vikrama Simhapuri University, Nellore (Andhra Pradesh), India.
2Ande Prasad, Professor, Department of Computer Science, Vikrama Simhapuri University, Nellore (Andhra Pradesh), India.
Manuscript received on March 05, 2020. | Revised Manuscript received on March 12, 2020. | Manuscript published on March 30, 2020. | PP: 1-5 | Volume-6 Issue-8, March 2020. | Retrieval Number: 100.1/ijese.H2461036820 | DOI: 10.35940/ijese.H2461.036820
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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 huge developments in touch screen devices and used in Computer vision developed the methodologies for recovering the images based on content. However in certain situations narration is the best suitable way to express and hence in the views of narration sketch based images are thus developed and utilized. These sketch based images are most useful in identifying face in criminal investigations. This paper provides a methodology for retrieving such sketch based images using the correlation based matching and generalized gamma mixture models. Performance is measured using precision and recall.
Keywords: Correlation Based Matching, Statistical Models, Criminal Investigations, Sketch-Based Images, Experimental Evaluation, Content Based Retrievals.