Volume 38, Number 6, December 2020
|Page(s)||1218 - 1224|
|Published online||02 February 2021|
Research on Low-Resolution Pattern Coding Recognition Method Based on Hu-DBN
School of Economics and Management, Hubei Engineering University, Xiaogan 432100, China
2 School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
3 Shaanxi Xueqian Normal University, Xi'an 710072, China
The feature image code represented by the two-dimensional code is the key reference for global positioning in the visual navigation of mobile robots. Although reducing the acquired low-resolution image helps to reduce the real-time performance of the algorithm, the acquired feature image is more susceptible to motion blur-based interference and affects the accuracy of recognition, which causes the positioning failure of the whole multi-intelligence, in which the body control system is invalid. In this paper, an optimized low-resolution feature image code recognition method is proposed. In the preprocessing part, the characteristic image is converted into the characteristic signal matrix of Hu invariant moments, and then the characteristic image is added to the characteristic signal matrix as a characteristic component, and then the Hu-DBN neural network signal classifier is used to construct the signal matrix so as to achieve accurate recognition of low-resolution custom image signature images under high motion tolerance conditions. It not only avoids the problem of classical pattern recognition relying on model experience and poor adaptability of the scene, but also avoids the problem of high computational complexity and recognition efficiency of directly deep learning methods such as YOLO. The deployment of the mobile robot instance deployment test shows that the average recognition rate is of 96.3% at a resolution of 640×480@Pixs and motion speed of 0.5 m/s, which proves the effectiveness of the present method.
Key words: calibration plate recognition / low resolution dynamic image / Hu-invariant moment / point diffusion model / mobile robot
关键字 : 图像特征码 / 低分辨动态影像 / Hu不变矩 / 深度置信网络 / 移动机器人视觉定位
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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