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A Fast and Efficient Thinning Algorithm for Binary Images
Tarik Abu-Ain, Siti Norul Huda Sheikh Abdullah, Bilal Bataineh & Khairuddin Omar
Pattern Recognition Research Group, Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia.
Email: tabuain@siswa.ukm.edu.my
Abstract. Skeletonization “also known as thinning” is an important step in the pre-processing phase in many of pattern recognition techniques. The output of Skeletonization process is the skeleton of the pattern in the images. Skeletonization is a crucial process for many applications such as OCR and writer identification. However, the improvements in this area are only a recent phenomenon and still require more researches. In this paper, a new skeletonization algorithm is proposed. This algorithm combines between parallel and sequential, which is categorized under an iterative approach. The suggested method is conducted by experiments of benchmark dataset for evaluation. The outcome is to obtain much better results compared to other thinning methods that are discussed in comparison part.
Keywords: skeletonization; thinning; document image analysis; text images; OCR.
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