Classification of Coral Reef Components Using Color and Texture Features
Keywords:
Coral Reef Classification, Hue Saturation Value Color, Local Binary Pattern, Multi-layer Perceptron Neural Network,Abstract
This paper presents classification of coral reef benthic components that composed of live corals, dead corals, rubbles and sands. Since coral reef exist with different of shapes, colours and textures, the use of image processing technique provides advantages to estimate percentage cover of coral reef benthic components. Color and texture are used to extract features of coral reef benthic components. Hue Saturation Value (HSV) color model is utilized by calculating its color histogram to obtain color features. Meanwhile, the Local Binary Pattern (LBP) descriptor is used to extract texture features. The color and texture features are combined as the input into the Multilayer Perceptron Neural Network (MLPNN) classifier. The performances of the coral reef classification are evaluated based on color feature, texture feature or combination of both color and texture features. It is found out that the joining feature set of color and texture features provide the highest classification accuracy, i.e. 92.60% accuracy rate as compared to the use of individual feature such as color and texture features alone that achieved only 81.30% and 88.10% accuracy classification rate, respectively.Downloads
Published
How to Cite
Issue
Section
License
TRANSFER OF COPYRIGHT AGREEMENT
The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):
- All proprietary right other than copyright, such as patent rights
- The right to make further copies of all or part of the published article for my use in classroom teaching
- The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
- The right to make copies of the published work for internal distribution within the institution that employs me
I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.