A Review of Image Segmentation of Underwater Images Using Fuzzy C- Means Clustering

The underwater image segmentation is a challenging field of research due to poor illumination condition. Therefore this paper reviews the various issues and problems based on the existing researches in underwater segmentation field. Since underwater images have many uses in general purposes like in marine engineering, analysis and monitoring of underwater animals and plants and for monitoring of oil wells. Thus, underwater segmentation problem can be considered as fuzzy problem. Therefore this paper reviews the fuzzy clustering algorithm for image segmentation. Fuzzy C-Means clustering based underwater image segmentation methods separates the underwater objects using clustering and thresholding. It is found that fuzzy based approaches are not such efficient in underwater environment and thus not much explored. The efficiency of the fuzzy based methods various with different images and objects. Paper pointed out various challenges after reviewing the previous work. It is require improving the efficiency of the fuzzy based systems for segmenting the underwater images.