Computer Vision based Vehicle Recognition on Indian Roads
Radhesyam Vaddi, Boggavarapu L. N. Phaneendra Kumar, Koteswara Rao Anne, V. R. Siddhartha · 2015
Feature extraction and classication are two most important modules for any vision-based object recognition system. In the case of vehicles, most of the methods in these modules found to be less accurate in recognition even though they work well for other objects. We are interested in recognition of vehicles on Indian roads. There are number of challenges in implementing vehicle recognition in Indian scenario like bad road conditions, trac rules violation and variance among vehicles, etc. In order to overcome these diculties, we implemented feature extraction module using bag of features (combination of Harris-corner detector and SIFT features), and classication is performed using Support vector machines (SVM). To validate our proposed method, we have introduced Indian Vehicle Database. The images in this database are extracted from daylight Indian urban trac scenes. Our proposed method achieves 40-45 percent improvement over the baseline methods.