Image Recognition of Steel Plate Defects Based on 3D Gray Matrix
Objective There are many kinds of surface defects and complicated gray structure in steel plate. The existing image segmentation technology has some shortcomings in the image recognition of steel plate defects. This paper proposes a surface defect recognition algorithm based on the spatial characteristics of 3D gray matrix. Method Firstly, a three-dimensional gray matrix is constructed according to the gray image; then a half-class variance improved Kriging interpolation algorithm is introduced to draw the contour map of the three-dimensional gray matrix; then the topological relationship tree of the contours is constructed; finally, the customized global search strategy and the local search strategy are combined to find the local concave and convex areas, thereby locating the defect area and achieving the purpose of dividing the surface defects of the steel plate. Result By testing the defect images of four types of steel plates, such as oxidation, roll printing, crusting and air bubbles, compared with other steel plate defect segmentation algorithms from the aspects of segmentation effect and evaluation indicator, this method can identify defect areas more effectively and is not sensitive to illumination changes. Under the premise of ensuring a low error rate, the effective segmentation rate is improved. Conclusion The steel plate defect image recognition algorithm based on three-dimensional gray matrix can effectively identify many types of steel plate defects, even in the image recognition with complex defect structure.