Friday 17th of November 2017
 

An Improved Cost-Efficient Thinning Algorithm for Digital Image


Liang Jia and Zhenjie Hou

Digital image processing plays an important role in our ever-evolving ubiquitous information society with an increasing need of automatic and efficient information collection. Thinning algorithms have been widely developed and applied in Optical Character Recognition (OCR) to eliminate the redundant data as well as keep the essential features of digital images. Inspired by the in-depth analysis of results obtained from Daviess classical algorithm, this paper proposes an improved and cost-effective thinning algorithm to enhance the accuracy of digital image skeletonization and also maintain the computation complexity at a low level. The extensive experiments show that the results of this improved thinning algorithm is able to achieve the similar accuracy of other advanced algorithms and inherits the advantage of low complexity of Daviess classical algorithm.

Keywords: Skeletonization, Thinning Algorithm, Medial Axis, Binary Image Processing, Image Erosion

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ABOUT THE AUTHORS

Liang Jia
He is a faculty member at Changzhou university of Jiangsu province in China. He received the MS degree in computer science from the Nanjing university of Science and Technology in 2009 and the BS degree in computer science from Beifang university of Nationalities in 2004. His research interests mainly include image processing, computer vision and database application development.

Zhenjie Hou
He was born in Hohhot, China. He received PH.D degree in 2005. His research interests include digital image processing, 3D reconstruction and virtual reality.


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