Dynamic wood slice recognition using image blur information

Abstract Image motion blur and defocus blur often occur when there is a relative motion between the imaging camera and the detected object. In this paper, we propose a robust wood slice recognition scheme using the low quality color wood slice images with the above-mentioned image blurs. First, a novel 2-D image measurement machine is devised, to obtain the object images sequentially by using a color camera. Second, the image-moment-based blur invariant features are calculated. Third, wood slice recognition is performed by using the computed Euclidean distance based on the moment invariants. We have experimentally proved that the effective use of image blur information improves the recognition accuracy of camera-captured wood slices. Moreover, the allowed maximum translation speed of the moving gallery is also discussed theoretically and experimentally. This scheme can identify the wood species by means of the slice recognition so as to judge the physical property and economic value of different wood species correctly.