CWT-based detection of roadside vegetation aided by motion estimation

In this paper we present a method for roadside vegetation detection intended for traffic safety and road infrastructure maintenance. While many published methods are using Near Infrared images which are suitable for vegetation detection, our method uses features from the visible spectrum allowing the use of a common color camera. The presented method uses a set of carefully selected color and texture features. Texture features are based on two-dimensional Continuous Wavelet Transform with oriented wavelets. Because texture can vary as the distance from the camera varies, we limit detection to the regions closer to the camera. We use optical flow as an approximate estimator of distance. The classification is done using nonlinear SVM. For training and testing purposes we recorded our own video database which contains roadside vegetation in various conditions. We present promising experimental results as well as a comparison with several alternative approaches.