Generalizing Laplacian of Gaussian Filters for Vanishing-Point Detection

We propose a framework for road-vanishing-point detection based on a new generalized Laplacian of Gaussian (gLoG) filter. In the first part, the gLoG filter can be applied to estimate the texture orientation at each pixel of an image, and the road vanishing point can be detected based on the estimated texture orientations. However, such a texture-based road-vanishing-point detection scheme suffers from high computational complexity. In the second part, an efficient gLoG-based road-vanishing-point detection method is proposed by only using the dominant texture orientations estimated at a sparse set of salient microblob road regions, where the gLoG filter is used to detect these salient microblob areas and simultaneously estimate their dominant texture orientations. Experimental results on 1003 general road images show that the efficient gLoG-based method is significantly faster than a Gabor-filter-based method, whereas the detection accuracy is comparable. The nonefficient gLoG-based method is more accurate in detecting the vanishing point than the Gabor-based approach.