Self-adaptive multi-scale weight morphological operator applied to wood products defects testing by using computed tomography

Abstract

Mathematical morphology is the emerging theory and method in digital image processing now. Based on the basic theory and algorithm of mathematical morphology, self-adaptive multi-scale weight morphological operator was advanced and used in the defect identification of wood products X-ray computed tomography image. As can be seen in the experimental analysis, compared with the traditional edge detection algorithm, self-adaptive multi-scale weight morphological operator had the characteristics of a high degree of detection and identification accuracy in wood products edge detection. Wood Products non-destructive testing real-time imaging hardware and wood products real-time imaging image processing software system were built in the study. And self-adaptive multi-scale weight morphological operator was used to edge detection of wood products X-ray image. The achievements in the study realized the real-time online detection of wood products X-ray computed tomography image, and improved the detection accuracy of defects in the image. They have a wide range of applications in the quality identification of wood board and defects detection in the logs.