Traffic Sign Detection via Graph Based Ranking and Segmentation Algorithm
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 66 | Views: 297

Research Paper | Computer Science & Engineering | India | Volume 9 Issue 12, December 2020 | Popularity: 6.5 / 10


     

Traffic Sign Detection via Graph Based Ranking and Segmentation Algorithm

Premsai Cheedella


Abstract: The majority of the existing traffic sign detection systems to utilize color or shape information, but the methods of remain limited in regard to detecting and segmenting traffic signs from a complex background. In this paper, we propose a novel graph-based traffic sign detection for an approach that consists of a saliency measure stage, a graph-based ranking stage, a multi threshold segmentation stage. Because the graph-based ranking algorithm with their specified color and saliency combines the information of color, saliency, spatial, and contextual relationship of the nodes, and more discriminative and robust than the other systems in terms of their handling various illumination conditions, and shape rotations, and scale changes from traffic sign images.


Keywords: Classification, detection, road sign, support vector machine SVMs


Edition: Volume 9 Issue 12, December 2020


Pages: 1615 - 1620



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Premsai Cheedella, "Traffic Sign Detection via Graph Based Ranking and Segmentation Algorithm", International Journal of Science and Research (IJSR), Volume 9 Issue 12, December 2020, pp. 1615-1620, https://www.ijsr.net/getabstract.php?paperid=SR201224141514, DOI: https://www.doi.org/10.21275/SR201224141514

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