Orientation estimation for planar textured surfaces based on complex wavelets

The gradient of a road or terrain influences the appropriate speed and power of a vehicle traversing it. Therefore, gradient prediction is necessary if autonomous vehicles are to optimise their locomotion. This paper presents a novel texture-based method for estimating the orientation of planar surfaces under the basic assumption of homogeneity. Based on a backprojection technique, we propose a new method for measuring texture consistency in the Dual-Tree Complex Wavelet Transform (DT-CWT) domain. Texture histograms computed with a new anti-aliasing compensation approach are employed to find the rotation of a planar surface. The proposed method performs well with various types of textured surfaces and outperforms other existing methods with significantly reduced computational complexity up to 35%.