Abstract
Virtual reality (VR) is based on graphics, images and sensors, and its simulation environment is a real-time and dynamic three dimensions realistic image generated by computer. The detection and extraction method of image edge and contour features is one of the research contents and hotspots in image detection, processing and analysis. Based on the traditional edge detection algorithm, in this paper a dynamic weight edge detection method based on multi-operator is proposed, an image edge detection system based on VR is developed, and the proposed algorithm is compared with the traditional method from the aspects of continuity, smoothness, edge width, positioning accuracy and system performance of the edge. The results indicate that this algorithm is the optimization and supplement of the traditional edge detection algorithm, has certain advantages in continuity and positioning accuracy, and can achieve rapid detection of VR image edge, which provides a theoretical basis for the research of VR image processing in the future.
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Acknowledgements
This paper is supported by grants from the National Natural Science Foundation of China (71731010, 71671048), the Natural Science Foundation of Guangdong Province (2015A030310506), the Philosophy and Social Science Planning Program of Guangdong Province (GD16XGL38), and the Philosophy and Social Science Planning Program of Guangzhou (2016GZQN32).
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Chen, Y., Wang, D. & Bi, G. An image edge recognition approach based on multi-operator dynamic weight detection in virtual reality scenario. Cluster Comput 22 (Suppl 4), 8069–8077 (2019). https://doi.org/10.1007/s10586-017-1604-y
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DOI: https://doi.org/10.1007/s10586-017-1604-y