文件名称:Image Segmentation Using Iterative Watersheding
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This paper presents a novel segmentation algorithm for metallographic images, especially those objects without regular boundaries and homogeneous intensity. In metallographic quantification, the complex microstructures make the conventional approaches hard to achieve a satisfactory partition. We formulate the segmentation procedure as a new fr a mework of iterative watershed region growing constrained by the ridge information. The seeds are selected by an effective double-threshold approach, and the ridges are superimposed as the highest waterlines in watershed transform. To tackle the over-segmentation problem, the blobs are merged iteratively with the utilization of Bayes classification rule. Experimental results show that the algorithm is effective in performing segmentation without too much parameter tuning.
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压缩包 : grid_segmentation.zip 列表 Iterative Watersheding.pdf grid segmentation/ grid segmentation/Thumbs.db grid segmentation/test.m grid segmentation/startup.m grid segmentation/readme.txt grid segmentation/ridge/ grid segmentation/ridge/im_hessangle2.m grid segmentation/ridge/im_hessstrflt2.m grid segmentation/ridge/im_scalablehess2.m grid segmentation/ridge/nonmaxsup.m grid segmentation/ridge/bwridgecenter.m grid segmentation/ridge/RemovePseudoContour.m grid segmentation/ridge/ModifyWaterShed.m grid segmentation/ridge/MarkPseudoBlob.m grid segmentation/ridge/gray2bw.m grid segmentation/ridge/dspimcat.m grid segmentation/ridge/dspimanalys.m grid segmentation/ridge/dspimalpha.m grid segmentation/ridge/DrawEllipse.m grid segmentation/ridge/DepthMeature.m grid segmentation/data1/ grid segmentation/data1/wkd01.jpg grid segmentation/data1/wkd02.jpg grid segmentation/data1/wkd03.jpg grid segmentation/data1/wkd04.jpg grid segmentation/data1/wkd05.jpg grid segmentation/data1/result/ license.txt