The Image Skeleton Extraction Algorithm Based on Highest Rectangle

Wei Qing Wang

doi:10.4028/www.scientific.net/AEF.1.283

Paper Titles

Study on the Algorithm for Real-Time Interpolation of NURBS Curve
p.262

Root Node Vaccines for Bayesian Network Structure Learning Based on Immune Algorithm
p.268

Improving the Performance of Process Controllers Using a New Clustered Neural Network
p.273

The Image Filtering Algorithm Based on the Enlarged Pixel Domain
p.278

The Image Skeleton Extraction Algorithm Based on Highest Rectangle
p.283

Study on Route Stability Based on the Metrics of Local Topology Transformation Entropy in Mobile Ad Hoc Networks
p.288

A Hierarchical Key Management Scheme in Mobile Ad hoc Networks
p.295

An Intelligent Storage Determining Method for Unloaded Containers in a Cycling Trailer Deployment Mode
p.300

Indexing Associated Knowledge Flow on the Web
p.305

HomeAdvanced Engineering ForumAdvanced Engineering Forum Vol. 1The Image Skeleton Extraction Algorithm Based on...

The Image Skeleton Extraction Algorithm Based on Highest Rectangle

Abstract:

Currently, the thinning algorithms based on the template have no completeness, so there are more error-retention and error-deletion pixels in their thinning results. In this article, using the highest rectangle which can not be eliminated, we put forward a new image-skeleton-extraction algorithm. Because the highest rectangle has completeness, there are no error-retention and error-deletion pixels in its thinning results. The algorithm can effectively eliminate the fracture phenomenon that is generated in the traditional algorithm. At the same time, the skeleton-thinning width is only one pixel, and it achieved to the ideal state. Experiments proved that the thinning result of this algorithm is more effective, and its operational efficiency is better.

By email View Pdf

You have full access to the following eBook

Emerging Engineering Approaches and Applications

Read eBook

Info:

Periodical:

Advanced Engineering Forum (Volume 1)

Pages:

283-287

DOI:

https://doi.org/10.4028/www.scientific.net/AEF.1.283

Citation:

Cite this paper

Online since:

September 2011

Authors:

Wei Qing Wang

Keywords:

Highest Rectangle, Image Segmentation, Image Thinning, Skeleton Extraction

Export:

RIS, BibTeX

Permissions:

Creative Commons CC BY 4.0

Citation:

References

[1] Wu Shuang, Zhang Yifei, Xiu Fei, Wang Daling, Bao Yubin, and Yu Ge． An Interest Point Based Feature Extraction Method for Medical Image Classification[J]． Journal of Computer Research and Development． 2007(suppl): 429-334.

Google Scholar

[2] ZHU W ei-feng, LI dun-li, W EI Ping． Segm entation of m edical im age based on the grey relational analysis[J]． OPTICAI TECHNIQUE． 2007(suppl): 429-334.

Google Scholar

[3] W ang Peng, Zhang Youguang, Zhang Shuo． A Synthetically Thinning Alg0rithm f0r Fingerprint Image[J]． J0URNAI 0F C0MPUTER—AIDED DESIGN ＆ C0MPUTER GRAPHICS． 2009, 21(2): 179-189.

Google Scholar

[4] Feng xingkui， I i I inyan， Yan Z uquan． A new thinning algorithm f0r fingerprint image[J]． Journa1 of Image and Graphics：A ，l999，4(10)：835—838 (in Chinese).

Google Scholar

[5] Wang Yelin, Ning xinbao, Yin Yilong． study on the fingerprint image thinning a1gorithm[J]． Journal of Nanjing University：Natural Sciences, 2003, 39(4)： 468-475 (in Chinese).

Google Scholar

[6] Wang Jialong，Guo Cheng'an． An improved Image template thinning algorithm[J]． Journal of Image and Graphics： A, 2004, 9(3)：297-301(jn Chjnese).

Google Scholar

[7] YANG Fan, ZHAO Shun-dong. Effective mixed fingerprint image quick thinning algorithm[J]. Application Research of Computers. 2008, 25(1): 3034-3035.

Google Scholar

[8] MEI Yuan, SUN Huai-jian, XIA De-shen. An Improved Template-based Rapid Thinning Algorithm[J]. Journal of Image and Graphics. 2006, 11(9): 1306-1311.

Google Scholar