Published Paper Details:

This paper represents that an efficient method for reliably detecting road lanes based on spatiotemporal images. In an aligned spatiotemporal image generated by accumulating the pixels on a scanline along the time axis and aligning consecutive scanlines, the trajectory of the lane points appears smooth and forms a straight line. The aligned spatiotemporal image is binarized, and two dominant parallel straight lines resulting from the temporal consistency of lane width on a given scanline are detected using a Hough transform, reducing alignment errors. Lane detection is normally helpful to localize road boundaries, determine undesired lane variations, and to enable approximation of the upcoming geometry of the road. There are different types of methods that are used for detecting lines, curves and ellipses i.e. hough transform, clustering and curve fitting. The overall objective of this paper is to providing better performance in lane coloration algorithm. The methods developed so far are working effectively and giving good results.