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Image segmentation, as a key technology in digital image processing, serves as the basis for image processing and analysis and understanding. Its main purpose is to separate useful image information (i.e. foreground) from useless image information (i.e. background) in some way. With segmentation of clothing image in online shopping as the center, this paper studied image segmentation technology. Study and analysis of a large number of online clothing images found that image clothing can be roughly divided into two categories. The first is simply displayed clothing without human model, with several clothing displayed together. The other is image with human model. By distinguishing the two types of images with face detection algorithm and edge detection method, applying different location algorithms for the two types of images, and adjusting image location with iterative algorithm, ultimately, more accurate localization frames were obtained, which can replace the part in traditional classical GrabCut algorithm that requires manual participation, and realize automatic batch operation of image segmentation. The final test data proved effectiveness of the new improved algorithm which can be applied in retrieval system of mass images at the time of online clothing shopping.

Pre-detection Technology of Clothing Image Segmentation Based on GrabCut Algorithm