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To solve the problem of wood skin recognition and classification in wood processing industry, a method based on BOW model for image recognition of wood skin defects is proposed. First, we extract the HOG feature of wood skin defect image, and then build the BOW model to describe the wood skin defect image. Finally, we use different kernel functions combined with support vector machine (SVM) to identify the types of wood skin defects. The experimental results show that the average recognition rate of the proposed method is 85.4% for wood skin defect image recognition and classification, indicating that the BOW model is effective and feasible for wood skin defect image recognition and classification.

Study on Image Recognition and Classification of Wood Skin Defects Based on BOW Model