Survey on Content-Based Image Segmentation Methods
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National Natural Science Foundation of China (61373012, 91218302, 61321491, 61373059); Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (15KJB520016); Natural Science Foundation of Jiangsu Province (BK20150016)

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    Abstract:

    Image segmentation is the process of dividing the image into a number of regions with similar properties, and it's the preprocessing step for many image processing tasks. In recent years, domestic and foreign scholars mainly focus on the content-based image segmentation algorithms. Based on extensive research on the existing literatures and the latest achievements, this paper categorizes image segmentation algorithms into three types:graph theory based method, pixel clustering based method and semantic segmentation method. The basic ideas, advantage and disadvantage of typical algorithms belong to each category, especially the most recent image semantic segmentation algorithms based on deep neural network are analyzed, compared and summarized. Furthermore, the paper introduces the datasets which are commonly used as benchmark in image segmentation and evaluation criteria for algorithms, and compares several image segmentation algorithms with experiments as well. Finally, some potential future research work is discussed.

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姜枫,顾庆,郝慧珍,李娜,郭延文,陈道蓄.基于内容的图像分割方法综述.软件学报,2017,28(1):160-183

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History
  • Received:June 16,2016
  • Revised:September 07,2016
  • Adopted:
  • Online: November 10,2016
  • Published:
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