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Research on Recognition Method of Truck Brand Types Based on Machine Learning

Aiming at the problem that truck brand type recognition is easily affected by complex scenes and illumination changes, this paper studies the truck brand type recognition method based on machine learning. The feature extraction method-Scale-Invariant Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) are compared and analyzed. Then different kernel functions of support vector machine classifier such as Linear Kernel, Gaussian Kernel, Sigmoid Kernel, Polynomial Kernel and Laplace Kernel are proposed and analyzed. Based on the truck face image set of Southeast University, a comparative experimental study is carried out. The theoretical analysis and experimental results show that: Based on HOG feature and Linear Kernel function, the performance of truck brand type recognition method based on support vector machine is better than the other four methods, and its recognition accuracy reaches 89.63%.