Abstract
This paper presents the implementation as well as simulated results of the enhanced algorithm for obstacle detection and avoidance using a hybrid of plane to plane homography, image segmentation, corner and edge detection techniques. The key advantages of this algorithm over similar ones are: (i) elimination of false positives obtained by the image segmentation technique as a result of which obstacle detection becomes more efficient, (ii) reduction in the presence of unreliable corners and broken edge lines in high resolution images which may result in poor homography computation and image segmentation respectively, (iii) elimination of lack of depth perception hence the system provides and evaluates depth and obstacle height properly without planar assumptions, (iv) significant reduction in processing power.
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