Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Automated GrowCut with Multilevel Seed Strength Value for Building Image
Dai UenoHiromi YoshidaYouji Iiguni
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2016 Volume 29 Issue 6 Pages 266-274


In this paper, we propose an automated GrowCut method for building extraction from scenery images. GrowCut achieves a high-performance for image segmentation to a wide variety of images,but its quality of segmentation depends largely on accuracy of user-specified seed pixels. Therefore, if seed pixels are specified automatically and accurately, GrowCut can be employed as a promising method for automatic building extraction. The proposed method uses a priori knowledge that target is a building, in order to specify seed pixels automatically and accurately. Moreover, it also achieves a higher repeatability in building extraction than the conventional method by introducing multi-level seed strength in GrowCut.

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© 2016 The Institute of Systems, Control and Information Engineers
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