A Fuzzy Adaptive Segmentation Algorithm for Moving Impurity in Liquid Video Sequences

The effective segmentation of moving impurity in liquid plays a key role in automatic detecting system.A fuzzy adaptive segmentation algorithm of moving impurity in liquid based on spatial block variance and its gradient is proposed.At first,two difference images from 4 consecutive frames are partitioned into 5×5 small blocks respectively,and then the homologous block variance and its gradient are computed,and their product is used as the block feature to construct a new image.After that,an adaptive thresholding is used to segment the new image.To cope with the changes of the block grey value,a fuzzy inference method is adopted to adjust the threshold adaptively according to the block variance and its gradient.The experimental and factual testing results show that the proposed algorithm is practical,effective,and can meet the demands of real-time detection of moving impurity in liquid