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Proceedings Paper

A fuzzy system approach for the classification of underwater AUV color images
Author(s): José A. Díaz; Raúl E. Torres
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Paper Abstract

This paper presents a fuzzy system approach using texture and color to classify living coral cover in underwater color images acquired by an autonomous underwater vehicle (AUV). The proposed fuzzy system for classification consists in the assigning of fuzzy memberships to different image features such as the mean, the spatial variance, the Gabor filter response standard deviation, and the wavelet energy. These fuzzy sensors are applied to the different segments present in the images. The segmentation of the images is previously done using the Homogeneity Coefficient Segmentation Algorithm (LHC). The resulted classification of the regions is compared against ground truth maps of the images. A correct classification over 80% was achieved in two different 25 images sets of two different areas.

Paper Details

Date Published: 27 February 2007
PDF: 8 pages
Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 649711 (27 February 2007); doi: 10.1117/12.704680
Show Author Affiliations
José A. Díaz, Univ. of Puerto Rico Mayagüez (United States)
Raúl E. Torres, Univ. of Puerto Rico Mayagüez (United States)


Published in SPIE Proceedings Vol. 6497:
Image Processing: Algorithms and Systems V
Jaakko T. Astola; Karen O. Egiazarian; Edward R. Dougherty, Editor(s)

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