Vehicle Wheel Hub Recognition Method Based on HOG Feature Extraction and SVM Classifier

In order to avoid the problems of low accuracy of wheel hub recognition and classification and excessive dependence on template image quality in the process of automatic production of the automobile wheel hub, a vehicle wheel hub recognition method based on Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) is proposed. Firstly, the wheel hub images under three different lighting conditions are collected, and the wheel hub images are processed in grayscale; Secondly, the positive and negative samples are made, and hog features are extracted, respectively; Finally, the extracted hog features are trained by SVM classifier, and the trained target classifier is used to recognize the wheel hub photos under three different lighting conditions. The experimental results show that this method has higher recognition accuracy than the traditional template matching method under different lighting conditions.