کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
535276 | 870336 | 2015 | 8 صفحه PDF | دانلود رایگان |
• We present a novel wavelet-based fuzzy multiphase image segmentation model.
• By introducing PCA features data, the proposed model can segment texture images.
• We formulate a fast iterative shrinkage algorithm for multiphase image segmentation.
• Experimental results show the effectiveness of the proposed method.
This letter proposes a novel fuzzy multiphase image segmentation model. In the model, we introduce wavelet based regularization on the membership functions which are used as indicators of different regions. By using principal component analysis (PCA) features data as descriptors, the proposed model can segment texture and natural images. To efficiently solve the model, we formulate a fast iterative shrinkage algorithm for multiphase image segmentation. Experimental results show that the proposed method achieves better segmentation results compared with some other classical variational segmentation methods.
Journal: Pattern Recognition Letters - Volume 53, 1 February 2015, Pages 1–8