Abstract: The mission of the vision system of autonomous underwater vehicle(AUV) is dealing with the information about the object in the complex environment rapidly and exactly for AUV to use the obtained result for the next task.So, aiming at realizing the image segmentation quickly on the precondition of high qualification, a fast fuzzy C-means algorithm based on entropy constraint for underwater image segmentation was proposed, in which the gradient operator,the histogram' s statistical characterization, sampling-computation and the relative information loss were considered comprehensively, and regularity of taking value of fuzzy weighted exponent m in this new algorithm was studied in detail by use of underwater image segmentation result and appraisal index of validity of fuzzy partition. Experimental results show that the novel algorithm can get a better segmentation result and the time efficiency is improved and the request of highly real-time effectiveness of AUV is satisfied.

Key words: Underwater image segmentation,Autonomous underwater vehicle(AUV)，Relative information loss, Fuzzy partition,Weighted exponent,Real-time effectiveness