Content based Image Retrieval System using Combination of Color and Shape Features, and Siamese Neural Network
R Rajkumar1, M V Sudhamani2
1Mr. R Rajkumar, Assistant Professor, Department of ISE, RNSIT, Bengaluru (Karnataka), India.
2Dr. M V Sudhamani, Dean-R&D, Professor and HOD, Department of ISE, RNSIT, Bengaluru (Karnataka), India.
Manuscript received on 03 December 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 31 December 2019 | PP: 71-77 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10531292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1053.1292S19
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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: With an advent of technologya huge collection of digital images is formed as repositories on world wide web (WWW). The task of searching for similar images in the repository is difficult. In this paper, retrieval of similar images from www is demonstrated with the help of combination of image features as color and shape and then using Siamese neural network which is constructed to the requirement as a novel approach. Here, one-shot learning technique is used to test the Siamese Neural Network model for retrieval performance. Various experiments are conducted with both the methods and results obtained are tabulated. The performance of the system is evaluated with precision parameter and which is found to be high.Also, relative study is made with existing works.
Keywords: CBIR, Siamese Neural Network, One-Shot Learning, Color.
Scope of the Article: Neural Information Processing