Article: Zebra crossing detection based on HSV colour model and projective invariant for driver assistance system Journal: International Journal of Applied Pattern Recognition (IJAPR) 2019 Vol.6 No.1 pp.1 - 14 Abstract: This paper implements a colour and shape-based Zebra crossings detection model. As Zebra crossings are white coloured, a robust binarisation based on the V channel of the input image is used to find the large rectangle sized white stripes of Zebra crossing. After the morphological open operation, boundary tracing is done using Moore-neighbourhood tracing algorithm along with Jacob's stopping criterion. For every region, the bounding quadrilateral with the minimum area is computed and the candidate regions are then filtered out using some criteria, e.g., aspect ratio. The y-coordinates of the lower vertices of the white stripes are considered as 'cluster' and the optimal number of clusters is determined using the Calinski-Harabasz criterion. These clusters are now checked to determine whether they represent crosswalks and then validate using projective invariant. Various Zebra crossing images are used to test the proposed framework and the results are presented to prove its effectiveness. Inderscience Publishers - linking academia, business and industry through research

Title: Zebra crossing detection based on HSV colour model and projective invariant for driver assistance system

Authors: Muhammad Kamal Hossen; Mohammad Obaidur Rahman; Anika Sadia; Md. Shahnur Azad Chowdhury

Addresses: Department of Computer Science and Engineering, CUET, Chittagong-4349, Bangladesh ' Department of Computer Science and Engineering, CUET, Chittagong-4349, Bangladesh ' Department of Computer Science and Engineering, CUET, Chittagong-4349, Bangladesh ' Department of Business Administration, IIUC, Chittagong-4318, Bangladesh

Abstract: This paper implements a colour and shape-based Zebra crossings detection model. As Zebra crossings are white coloured, a robust binarisation based on the V channel of the input image is used to find the large rectangle sized white stripes of Zebra crossing. After the morphological open operation, boundary tracing is done using Moore-neighbourhood tracing algorithm along with Jacob's stopping criterion. For every region, the bounding quadrilateral with the minimum area is computed and the candidate regions are then filtered out using some criteria, e.g., aspect ratio. The y-coordinates of the lower vertices of the white stripes are considered as 'cluster' and the optimal number of clusters is determined using the Calinski-Harabasz criterion. These clusters are now checked to determine whether they represent crosswalks and then validate using projective invariant. Various Zebra crossing images are used to test the proposed framework and the results are presented to prove its effectiveness.

Keywords: zebra crossing; crosswalks; intelligent transport systems; HSV; region of interest; Moore-neighbourhood; bounding quadrilateral; K-means clustering; Calinski-Harabasz; projective invariant.

DOI: 10.1504/IJAPR.2019.104278

International Journal of Applied Pattern Recognition, 2019 Vol.6 No.1, pp.1 - 14

Received: 04 Jul 2018
Accepted: 03 Nov 2018
Published online: 02 Jan 2020 *

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Title: Zebra crossing detection based on HSV colour model and projective invariant for driver assistance system

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