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《Journal of Data Acquisition and Processing》 2018-02
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Application of New Local Watershed Model in Image Segmentation

Liu Haitao;Di Lan;Liang Jiuzhen;College of Digital Media,Jiangnan University;College of IoT Engineering,Jiangnan University;  
In order to improve the ability of image segmentation to grasp significant areas,an algorithm based on grid local watershed method and fuzzy C-means(FCM)is proposed by combing super pixel thoughts and watershed algorithm.The algorithm first partition an image into non-uniform grids according to the variance.For each grid,watershed algorithm is applied with the best gradient threshold to reduce the loss of local information in global watershed.In this way,the significant basins of each grid are extracted.Through regional integration and mean normalization of each area,FCM clustering considering the size of each region is used to get the final segmentation image.Experimental results show its great robustness against noise.In addition,the algorithm can effectively eliminate the interference regions and segment the significant regions of images with a low time complexity.
【Fund】: 江苏省六大人才高峰(DZXX-028)资助项目;; 江苏省产学研(BY2014023-33)资助项目
【CateGory Index】: TP391.41
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