NDLI: Image classification of coral reef components from underwater color video

Content Provider	IEEE Xplore Digital Library
Author	Soriano, M. Marcos, S. Saloma, C. Quibilan, M. Alino, P.
Copyright Year	2001
Description	Author affiliation: Nat. Inst. of Phys., Univ. of the Philippines, Philippines (Soriano, M.)
Abstract	The purpose of this study is to automate coral reef assessment, that is, to classify coral images into benthic categories from digitized underwater video using a computer-based classifier such that coral reef analysis becomes less subjective, less tedious and more precise. Corals exhibit a variety of color, texture and structure which are the visual cues used by marine scientists for their classification. In computer vision, color is a point property of a picture element while texture is a property of an area. Color and texture have been combined as color-texture which is a feature that describes the spatial organization of colors in an area. As inputs to a classifier, the authors extract color, texture and color-texture descriptors from coral images and measure recognition rates using each feature. Corals are 3D structures and, when imaged, are prone to varying resolutions, perspective projection and lighting conditions. Therefore, an additional objective of this study is to address the problem of illumination, rotation and scale invariance in pattern recognition of underwater images. Images were classified into one of five benthic categories: alive coral, dead coral, dead coral with algae, algae and abiotics. Overall, texture was found to be more discriminating than using color alone or color and texture combined. Dead coral was the most successfully recognized class using color features.
Starting Page	1008
Ending Page	1013
File Size	589691
Page Count	6
File Format	PDF
ISBN	0933957289
DOI	10.1109/OCEANS.2001.968254
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-11-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Marine Technology Soc.
Subject Keyword	Image classification Algae Pattern recognition Organisms Cities and towns Computer vision Image recognition Image resolution Lighting Sea floor
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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