Pseudo-Random Color Encoded 3D Characterization Technology In 3D Vision Detect

3D (three-dimensional) vision inspection based on machine vision theory has become an important measurement technique in on-line measurement field. The essential procedure of 3D vision inspection is to reconstruct the 3D dimensional coordinates of the object to be inspected from its images. In this process, however, there is a known difficult problem, i.e. the registration of correspondences between object surface and its images, and among images, especially for the free-form surface 3D reconstruction. In order to tackle this problem, active 3D vision inspections with structured light illumination, such as dot structured light, line structured light and encoded structured light pattern, are often employed in practical industry measurement. Among the varieties of structured light illumination, the most effective one is the encoded structured light pattern, because the 3D vision inspection system with this illumination method not only can be used for reconstructing the 3D coordinates of free-form surfaces, but also for dynamic or variable 3D scenes. Therefore, the research of the encoded structured light pattern to resolve the correspondence problem is very important in 3D vision inspection.In this paper, we concentrate our mind on a promising pseudo-random color encoded illumination pattern and its application. The illumination pattern has one of important characteristics, window property. Any feature point of the illumination pattern after emitted on the surface can be identified exclusively with respect to the window property of the pseudo-random color encoded array. The coordinates of the feature points on images can be obtained by Harris corner detector. Thus the correspondence problem depicted above can be readily solved.In the paper, the principle of the pseudo-random color encoded array, its illumination pattern feature extraction and research achievements in question are detailed. In summary, they are listed as follows:1. The principle of pseudo-random color encoded array is introduced. The differences of the illumination pattern from other illumination patterns are summarized. The program of the array pattern is given.2. The characteristics of the pseudo-random color encoded pattern with respect to its elements: color, shape and density of code are discussed.3. The algorithms of the image coordinate extraction of the pseudo-random color encoded pattern based on Harris corner detect and model matching method are implemented.