کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
495838 862841 2012 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fuzzy c-means clustering with weighted image patch for image segmentation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Fuzzy c-means clustering with weighted image patch for image segmentation
چکیده انگلیسی

Fuzzy c-means (FCM) clustering has been widely used in image segmentation. However, in spite of its computational efficiency and wide-spread prevalence, the FCM algorithm does not take the spatial information of pixels into consideration, and hence may result in low robustness to noise and less accurate segmentation. In this paper, we propose the weighted image patch-based FCM (WIPFCM) algorithm for image segmentation. In this algorithm, we use image patches to replace pixels in the fuzzy clustering, and construct a weighting scheme to able the pixels in each image patch to have anisotropic weights. Thus, the proposed algorithm incorporates local spatial information embedded in the image into the segmentation process, and hence improve its robustness to noise. We compared the novel algorithm to several state-of-the-art segmentation approaches in synthetic images and clinical brain MR studies. Our results show that the proposed WIPFCM algorithm can effectively overcome the impact of noise and substantially improve the accuracy of image segmentations.

Figure optionsDownload as PowerPoint slideHighlights
► Propose the weighted image patch-based FCM (WIPFCM) algorithm for image segmentation.
► Replace pixels with image patches to incorporate spatial information into clustering.
► Adaptively assign each pixel in an image patch a weight to reduce the impact of noise.
► Be more accurate and less sensitive to noise than eight FCM-based algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 12, Issue 6, June 2012, Pages 1659–1667
نویسندگان
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