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Road mark recognition using HOG-SVM and correlation
Author(s): Yousri Ouerhani; Ayman Alfalou; Christian Brosseau
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Paper Abstract

In this study we present a novel approach for road mark detection and recognition based on the commercial VIAPIX® module. The proposed approach combines two different techniques, an optical one based on correlation and a numerical technique based on the linear SVM (Support Vector Machine) classifier using HOG (Histogram of Gradient) as descriptor. The first step of our proposed approach consists to applying an inverse perspective mapping of the image acquired by the VIAPIX® module. Then, white color segmentation is applied in order to detect all road marks on the road. Next, a classification of the detected objects is performed using the correlation technique. Finally, the linear SVM technique is used for validating the recognized objects.

Paper Details

Date Published: 24 August 2017
PDF: 8 pages
Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103950Q (24 August 2017); doi: 10.1117/12.2273304
Show Author Affiliations
Yousri Ouerhani, ISEN Brest (France)
Actris (France)
Ayman Alfalou, ISEN Brest (France)
Christian Brosseau, Univ. de Brest, STICC (France)


Published in SPIE Proceedings Vol. 10395:
Optics and Photonics for Information Processing XI
Khan M. Iftekharuddin; Abdul A. S. Awwal; Mireya García Vázquez; Andrés Márquez; Víctor H. Diaz-Ramirez, Editor(s)

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