Title: A new framework for contour tracing using Euclidean distance mapping

Authors: S. Sobhana Mari; G. Raju

Addresses: Government Higher Secondary School, Pandi, Kasaragod, Kerala – 671 543, India ' Department of Data Science, Christ (Deemed to be University), Lavasa Campus, Pune, Maharashtra – 412 112, India

Abstract: In this paper, a new fast, efficient and accurate contour extraction method, using eight sequential Euclidean distance map and connectivity criteria based on maximal disk, is proposed. The connectivity criterion is based on a set of point pairs along the image boundary pixels. The proposed algorithm generates a contour of an image with less number of iterations compared to many of the existing methods. The performance of the proposed algorithm is tested with a database of handwritten character images. In comparison to two standard contour tracing algorithms (the Moore method and the Canny edge detection method), the proposed algorithm found to give good quality contour images and require less computing time. Further, features extracted from contours of handwritten character images, generated using the proposed algorithm, resulted in better recognition accuracy.

Keywords: contour tracing; Euclidean distance mapping; medical axis transform; handwritten character recognition.

DOI: 10.1504/IJCVR.2021.10040491

International Journal of Computational Vision and Robotics, 2021 Vol.11 No.5, pp.542 - 553

Accepted: 06 Jun 2020
Published online: 19 Aug 2021 *

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