A new framework for contour tracing using Euclidean distance mapping

Title

A new framework for contour tracing using Euclidean distance mapping

Creator

Sobhana Mari S.; Raju G.

Description

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. Copyright 2021 Inderscience Enterprises Ltd.

Source

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

Date

2021-01-01

Publisher

Inderscience Publishers

Subject

Contour tracing; Euclidean distance mapping; Handwritten character recognition; Medical axis transform

Coverage

Sobhana Mari S., Government Higher Secondary School, Pandi, Kasaragod, Kerala, 671 543, India; Raju G., Department of Data Science, Christ (Deemed to be University), Lavasa Campus, Maharashtra, Pune, 412 112, India

Rights

Restricted Access

Relation

ISSN: 17529131

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1504/IJCVR.2021.117584

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115278156&doi=10.1504%2fIJCVR.2021.117584&partnerID=40&md5=29a0ff319e94fa619620dccd6d0edae1