LANA: a lane extraction algorithm that uses frequency domain features

This paper introduces a new algorithm called Lane-finding in ANother domAin (LANA) for detecting lane markers in images acquired from a forward-looking vehicle-mounted camera. The method is based on a novel set of frequency domain features that capture relevant information concerning the strength and orientation of spatial edges. The frequency domain features are combined with a deformable template prior, in order to detect the lane markers of interest. Experimental results that illustrate the performance of this algorithm on images with varying lighting and environmental conditions, shadowing, lane occlusion(s), solid and dashed lines, etc. are presented. LANA seems to detect lane markers remarkably well under a very large and varied collection of roadway images. A comparison is drawn between this frequency feature-based LANA algorithm and the spatial feature-based LOIS lane detection algorithm. This comparison is made from experimental, computational, and methodological standpoints. Index Terms - Bayesian estimation, denoising, discrete cosine transform, global shape model, intelligent vehicles, likelihood ratio, number of operations.