Extraction of Features from a Bird's-Eye View for Path Detection | ||
| International Journal of Artificial Intelligence and Emerging Technology | ||
| Volume 6, Issue 1, June 2023, Pages 1-14 PDF (778.15 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ijaiet.2023.234712.1001 | ||
| Authors | ||
| Abdelmoty Ahmed1; Ahmed ElKattan2; Ahmed Omar3; Hammam Abdelaal4 | ||
| 1College of Computer Science, Nahda University in Beni Suef (NUB) | ||
| 2Surrey Business School, University of Surrey, Guildford, UK/ Faculty of Economics and Business, Complutense University of Madrid, Madrid, Spain | ||
| 3Department of Computer Science, Faculty of Science, Minia University, Egypt | ||
| 4Department of Information Technology, Faculty of Computers and Information, Luxor University | ||
| Abstract | ||
| Path detection has emerged as a complex challenge that has garnered significant attention within the computer vision community for a considerable span. The foundational problem of recognizing routes has evolved into a substantial impediment in the realm of computer vision. While a variety of Deep Learning methods have been employed for route identification, the focus has often centered on feature generation. Nonetheless, advanced Deep Learning techniques have exhibited proficiency in discerning these attributes. Yet, the complete implementation of these approaches to efficiently and accurately identify lanes is still pending. In this paper, we introduce an innovative perspective to address this issue. A distinctive approach to route preprocessing, coupled with a bird's-eye view, is presented. The primary aim involves the selection of the bird's-eye view area based on the processed image. Subsequently, an HSL (hue, saturation, and lightness) color transformation is applied to extract white features, along with a unique preliminary edge feature detection method. The lane is then identified using this new preprocessing strategy. It is noteworthy that numerous prior works have drawn upon the same standard datasets. | ||
| Keywords | ||
| Path Detection; leveraging preprocessing techniques; Bird' s-Eye View | ||
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