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  • 标题:Skeleton Generation for Digital Images Based on Performance Evaluation Parameters
  • 本地全文:下载
  • 作者:Prof. Gulshan Goyal ; Ritika Luthra
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:2
  • 页码:47-58
  • DOI:10.14257/ijsip.2016.9.2.05
  • 出版社:SERSC
  • 摘要:Skeletonization is a crucial step in many digital image processing applications like medical imaging, pattern recognition, fingerprint classification etc. The skeleton expresses the structural connectivities of the main component of an object and is one pixel in width. Present paper covers the aspects of pixel deletion criteria in the skeletonization algorithms needed to preserve the connectivity, topology, sensitivity of the binary images. Performance of different skeletonization algorithms can be measured in terms of different parameters such as thinning rate, number of connected components, execution time etc. Present paper focuses on Peak Signal to Noise Ratio, number of connected components, execution time and Mean Square error on Zhang and Suen algorithm and Guo and Hall algorithm.
  • 关键词:Skeletonization; Optical character Recognition (OCR); PSNR; MSE; ZS; ; GH
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