Scratches,oil stains,defects and lack of color on the surface of artificial wood board are key factors affecting product quality.Industrial automation production lines require online screening and sorting.Based on the high real-time requirements and the complexity of the defect background of artificial wood board,an artificial wood board defect detection algorithm based on multi-feature fusion is proposed in order to quickly and accu-rately identify its surface defects.The algorithm preprocessed the samples and obtained the color and texture fea-tures of the artificial wood board,established the corresponding feature data base,and compared and analyzed the extracted features of the board to be tested with the feature data base to achieve the purpose of defect detection.Aiming at the problem of feature matching prone to misjudgment,the cost complexity algorithm was used to build a feature data base for multiple features to realize multi-dimensional feature matching.The experimental results show that the detection method can accurately identify the surface defects of the board,and that the accuracy rate can reach 98％,which meets the basic requirements for the accuracy of automatic defect recognition in the indus-trial production of artificial wood board.The research results can provide a reference for the online defect detec-tion of artificial wood board.
维普
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