From Event: SPIE Optical Engineering + Applications, 2017
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.
Yousri Ouerhani, Ayman Alfalou, and Christian Brosseau, "Road mark recognition using HOG-SVM and correlation," Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103950Q (Presented at SPIE Optical Engineering + Applications: August 08, 2017; Published: 24 August 2017); https://doi.org/10.1117/12.2273304.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the conference proceedings. They include the speaker's narration along with a video recording of the presentation slides and animations. Many conference presentations also include full-text papers. Search and browse our growing collection of more than 12,000 conference presentations, including many plenary and keynote presentations.