Real-time illumination and shadow invariant lane detection on mobile platform
| Autor: | Ayhan Kucukmanisa, Gökhan Tarım, Oguzhan Urhan |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Maximally stable extremal regions
Computer science business.industry Template matching 020207 software engineering Advanced driver assistance systems 02 engineering and technology Computer graphics Outlier 0202 electrical engineering electronic engineering information engineering Preprocessor 020201 artificial intelligence & image processing Computer vision Artificial intelligence Invariant (mathematics) business Mobile device Information Systems |
| Zdroj: | Journal of Real-Time Image Processing. 16:1781-1794 |
| ISSN: | 1861-8219 1861-8200 |
| DOI: | 10.1007/s11554-017-0687-2 |
| Popis: | In this work, a novel lane detection method using a single input image is presented. The proposed method adopts a color and shadow invariant preprocessing stage including a feature region detection method called as maximally stable extremal regions. Next, candidate lane regions are examined according to their structural properties such as width–height ratio and orientation. This stage is followed by a template matching-based approach to decide final candidates for lane markings. At the final stage of the proposed method, outliers are eliminated using the random sample consensus approach. The proposed method is computationally lightweight, and thus, it is possible to execute it in real-time on consumer-grade mobile devices. Experimental results show that the proposed method is able to provide shadow, illumination and road defects invariant performance compared to the existing methods. |
| Databáze: | OpenAIRE |
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