Skeletonization of ribbon-like shapes based on local minimum modules of wavelet transform

Hu, Shigang; Xiong, Yanming; Liao, Melody Z. W.; Tang, Yuan Yan

doi:10.1109/icwapr.2007.4421625

Cited by 3 publications

(1 citation statement)

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“…The authors reviewed nearly 300 kinds of methods about skeletonization in [12]. No matter which method, a good skeleton should have the following properties [13][14]:…”

Section: Introductionmentioning

confidence: 99%

Curve-Skeleton Extraction Using Appropriate Threshold Optimization

Wang

Qiu

Song

2013

AMR

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The curve-skeleton of an object is an important abstract geometrical and topological representation of its shape, which is extremely useful for pattern recognition and computer vision applications involving in shape analysis. In this paper, we propose an effective algorithm for extracting curve skeleton based on the definition and properties of curve skeleton from pixel cloud, which integrates the advantages of the visual main parts reliability for object recognition and the skeletons reduced-dimension for object representation. This algorithm can detect each pixel of the image, and find the salience value of each pixel; the salience value is the possibility of the pixel being a skeleton point. Then an appropriate threshold is selected to pruning the skeleton and to get the curve skeleton. In this way, the algorithm can be effective in reducing the number of non-skeleton pixels, and reduce the overall time of extracting skeleton. The experiments show that the skeleton keeps the topology of the target. And the corners of the skeleton are smoother and more natural. In additionally, it can effectively reduce redundant branches of skeleton.

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“…The authors reviewed nearly 300 kinds of methods about skeletonization in [12]. No matter which method, a good skeleton should have the following properties [13][14]:…”

Section: Introductionmentioning

confidence: 99%