Coral Reef Image Classifications
Padma Priya1, S. Muruganantham2
1Padma Priya, Research Scholar, Department of Computer Science, S. T. Hindu College, Nagercoil (Tamil Nadu), India.
2Dr. S. Muruganantham, Associate Professor, Department of Computer Science, S. T. Hindu College, Nagercoil, Affliated to Manonmanium Sundaranar University, Tirunelveli (Tamil Nadu), India.
Manuscript received on 21 May 2019 | Revised Manuscript received on 07 June 2019 | Manuscript Published on 15 June 2019 | PP: 306-309 | Volume-8 Issue-1S2 May 2019 | Retrieval Number: A00710581S219/2019©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: This chapter presents various classification methods for resolving the coral reef which exhibit vital within-class variations, complicated between-class boundaries and discrepant image clarity. This makes coral classification a difficult task. In this paper we examine the recent activity of image classification approaches and techniques. Image classification is a difficult process which depends upon various factors. Here, we deliberate about the current procedures, obstacles as well as prospects of image classification. This main attention will be on advanced classification techniques which are used for improving classification accuracy. Additionally, some important problems relating to classification performance are also discussed. The aim of this paper is to report an illustrative and comparative study of the most popular feature extraction methods which are generally used for classification.
Keywords: Coral Reef, Classification, SVM, KNN, Decision Tree, Neural Network.
Scope of the Article: Image Security