Wei Sun1, 2, *, Xiaorui Zhang2, 3, Xiaozheng He4, Yan Jin1, Xu Zhang3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2489-2510, 2020, DOI:10.32604/cmc.2020.012343
Abstract Vehicle type recognition (VTR) is an important research topic due to its
significance in intelligent transportation systems. However, recognizing vehicle type on
the real-world images is challenging due to the illumination change, partial occlusion
under real traffic environment. These difficulties limit the performance of current stateof-art methods, which are typically based on single-stage classification without
considering feature availability. To address such difficulties, this paper proposes a twostage vehicle type recognition method combining the most effective Gabor features. The
first stage leverages edge features to classify vehicles by size into big or small via a
similarity k-nearest neighbor classifier (SKNNC). Further… More >
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