Abstract
With the development of wood industry and the large requirement for the wood surface processing quality,traditional artificial detections have been difficult for satisfying wood processing production requirement.By knowing the classification of wood surface defects,defect causes and characteristics of wood surface defect images,we compare and analyze the average method,maximum method and the weighted average method on image gray effect,and the weighted average method is selected.In Matlab 6.5GUI programming framework,we implement wood defect detection system by choosing the Isodata clustering iteration method,Otsu method of maximum variance,maximum entropy method and Sobel edge segmentation method for image segmentation and comparisons.We can achieve the fast and accurate image segmentation and wood material defect detection by using the Isodata clustering iteration method.
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