کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
533448 | 870118 | 2012 | 14 صفحه PDF | دانلود رایگان |
We show that the problem of extracting linear features from a noisy image and counting the number of branching points may be successfully solved by homological methods applied directly to the image without the need of skeletonization and the analysis of the resulting graph. The method is based on the superimposition of a mask set over the original image and works even when the homology of the feature is trivial and in arbitrary dimension. We tested the method on computer-generated data, 2D images of blood vessels, 2D satellite images and 3D images of collagen fibers.
► Extraction of linear features from a noisy image by homological methods in any dimension.
► Counting the number of branching points by homological methods in any dimension.
► Examples of application to 2D images of blood vessels, 2D satellite images and 3D images of collagen fibers.
Journal: Pattern Recognition - Volume 45, Issue 1, January 2012, Pages 285–298