Abstract
Image thinning is one of the fundamental pre-processing steps prior to the shape representation in the image analysis of printed and handwritten alphabet recognition applications. In this paper, an approach is introduced for the thinning of alphabet images using Delaunay Triangulation algorithms. Delaunay Triangulation is one of the most essential data structures in the field of Computational Geometry. Given a finite set of points that represent an image of an alphabet, the reconstruction of the alphabet using a simplified point set is studied. The performance of the proposed model evaluated by evaluating the Thinning Rate. The alphabet images of the Chara74K dataset were used to test the model and the average Thinning Rate was found to be 91%. It is demonstrated that the proposed model can be used for reconstruction of text images, broken alphabet images and Dot-Matrix alphabet images.
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Joseph, P., Kovoor, B.C., Thomas, J. (2020). Delaunay Triangulation Based Thinning Algorithm for Alphabet Images. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1147. Springer, Singapore. https://doi.org/10.1007/978-981-15-4015-8_25
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DOI: https://doi.org/10.1007/978-981-15-4015-8_25
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