Point-cloud lossless compression new algorithm by merging gray-coded structured light series patterns and compression of two-dimensional single channel matrix

According to the development of non-contact three-dimensional measurement methods over the past two decades, along with the acceleration of scanning operations and the accuracy in measuring and significant development of their application in a wide range of fields (such as design, reverse engineering, quality control and inspection, medicine, documentation of objects, robotics, etc.), we have seen an increase in the amount of information obtained (points cloud) from the 3D scanner as the output of the scan operation. This raises restrictions on data management, data transfer, data storage, or even the development of real-time scanning methods. In this way, the need to compress and reduce the amount of data with the preservation of accuracy or minimum drop in accuracy and quality as one of the issues of interest in the post-processing of scanning operations has been revealed more than ever before. In this paper with presenting a new and distinct method for lossless compression on points cloud obtained from 3D scan operations in the form of an ordinary single-channel 2D image based on the image-based encoding techniques, we have evaluated the performance and effectiveness of the proposed method, while designing and constructing a non-contact 3D scanner with structured-light pattern based on the Gray code technique. The results show the accuracy and applicability of this method and the achievement of distinct compression rate [230:1] among other lossless compression methods of 3D data.