Towards effective Content Based Image Retrieval based on Local Binary Patterns and Finite Beta Mixture Model
Subash Chandra Chadalavada1, Srinivas Yarramalle2
1Subash Chandra Chadalavada, Assoc. Prof., Department of CSE, Kakinada Institute of Engineering & Technology, Korangi, India.
2Srinivas Yarramalle, Professor, Department of IT, GITAM Institute of Technology, GITAM University, Vizag, India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 146-150 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6412048419/19©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: Content Based Retrievals has major role in many practical situations where the images are to be extracted based on the content. However, with the vast dimensionality of the data surrounding retrieval of the relevant information in minimum instance of time together with accuracy is a challenging task. This article presents an ideology to counter attack the challenge by proposing a model based on Finite Beta Mixture Distribution. In order to extract the Features, Local Binary Patterns (LBP) are considered and the proposed work is implemented based on Flickr Dataset
Keywords: CBIR, LBP, Dimensionality, Beta Mixture Model, Flickr.
Scope of the Article: Image Processing