Abstract

Despite the benefits derived from the development of 3D techniques to improve the acceleration and accuracy of 3D scanning operations over the past two decades and its wide range applications in various industries (e.g., quality control and inspection, reverse engineering, robotics), there are restrictions on data transfer, data storage, and even the development of real-time scanning methods due to the enlarging data size (point cloud). According to the importance of maintaining all the output data of the scanner in instrumentation engineering, the need to apply minimum loss or lossless data compression algorithms is more than ever evident. In this regard, this paper presents a novel method in point cloud lossless data compression, using a Gray code structured light pattern sequence and image-based compression. The empirical evaluation and results of the proposed method demonstrate that this idea is reliable and practical to achieve a distinct compression ratio among other lossless point cloud compression methods.

© 2018 Optical Society of America

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