Composite Method for Image Retrieval
D. Madhavi1, N. Jyothi2, Md. K. M. Chisti3
1D. Madhavi*, Associate professor, Department of EECE, GITAM Deemed to be University, Visakhapatnam, India.
2N. Jyothi, Associate professor, Department of EECE, GITAM Deemed to be University, Visakhapatnam, India.
3M. D. K. M. Chisti, Assistant professor, Department of EECE, GITAM Deemed to be University, Visakhapatnam, India.
Manuscript received on January 25, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 29, 2020. | PP: 4042-4045 | Volume-9 Issue-3, February 2020. | Retrieval Number: C6559029320/2020©BEIESP | DOI: 10.35940/ijeat.C6559.029320
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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: In the present day to day life the retrieval of images from the larger database has become important like Google search. Presently, CBIR is trending method. In this paper images are retrieved in three stages with color, texture and shape feature extracted in each respective stage. The color feature extraction is done through finding different parameters for an RGB image, combined texture feature extraction through Gray level co-occurrence matrix GLCM and Gabor filter and shape feature extraction through region growing. The experiment is done on images present in coral database. The simulation results have been compared and it has been shown that the proposed method show high retrieval rate in terms of the average precision and average recall.
Keywords: Image Retrieval, Gray level co-occurrence matrix (GLCM), Region growing.