¹School of Mechanical Engineering, Shandong University, Jinan, Shandong 250061, China
²School of Mechanical and Electronic Engineering, Zaozhuang University, Zaozhuang 277160,China

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Abstract—Traditional fuzzy clustering algorithm is applicable for noiseless image segmentation. However, it is powerless for the images with noise, special point values and defects. An algorithm which combines spatial fuzzy clustering and level set for indoor scene segmentation is proposed in this paper. Firstly, the image is classified using fuzzy clustering with space information to get a larger difference in image gray level; secondly, the image is segmented using level set; finally, the contour in the boundary of target area is gotten accurately. The improved method can not only preserve details of images but also reduce the number of iterations. The results show that the proposed method has good segmentation quality and efficiency in segmentation for indoor scene image.

Index Terms—spatial fuzzy c-means cluster; level set; indoor scene; image segmentation; fusion

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Cite: Jili Lu, Mingxing Lin, Qingdong Wang, Yan Huang, "An Integrated Algorithm of Spatial Fuzzy C-Means Clustering and Level Set for Indoor Scene Image Segmentation," Journal of Computers vol. 9, no. 4, pp. 1033-1039, 2014.