用于视觉测量的编码目标识别算法

IF 1 4区 计算机科学 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Peng Zhang, Qing Liu, Shengpeng Li, Fei Liu, Wenjing Liu
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引用次数: 0

摘要

环形编码目标作为待测特征点被广泛应用于三维测量、目标跟踪、增强现实等领域。传统的编码目标识别算法容易受到光照变化和拍摄角度过大的影响,识别精度明显降低。因此,需要一种新的编码目标识别算法来减少光照和角度对识别过程的影响。本文深入分析了光照对编码目标识别的影响,并讨论了传统算法的优缺点。设计了一种新的自适应阈值图像分割方法,与传统算法相比,该方法在确定图像分割阈值时纳入了编码目标的特征信息。实验结果表明,该方法显著降低了光照变化和杂乱背景对图像分割的影响。同样,还研究了不同角度对编码目标识别过程的影响。通过密集点网络的径向采样对编码目标进行解码,可以有效降低角度对识别过程的影响,提高编码目标的识别精度和算法的鲁棒性。此外,进一步的实验验证了所提出的检测和识别算法能更好地进行提取和识别,具有较高的定位精度和解码成功率。即使在复杂环境下也能实现精确定位,满足工业测量的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coded target recognition algorithm for vision measurement
Circularly coded targets are widely used in 3D measurement, target tracking, augmented reality, and other fields as feature points to be measured. The traditional coded target recognition algorithm is easily affected by illumination changes and excessive shooting angles, and the recognition accuracy is significantly reduced. Therefore, a new coded target recognition algorithm is required to reduce the effects of illumination and angle on the recognition process. The influence of illumination on the recognition of coding targets was analyzed in depth, and the advantages and disadvantages of traditional algorithms are discussed. A new adaptive threshold image segmentation method was designed, which, in contrast to traditional algorithms, incorporates the feature information of coding targets in the determination of the image segmentation threshold. The experimental results show that this method significantly reduces the influence of illumination variations and cluttered backgrounds on image segmentation. Similarly, the influence of different angles on the recognition process of coding targets was studied. The coding target is decoded by radial sampling of the dense point network, which can effectively reduce the influence of angle on the recognition process and improve the recognition accuracy of coding targets and the robustness of the algorithm. In addition, further experiments verified that the proposed detection and recognition algorithm can better extract and identify with high positioning accuracy and decoding success rate. It can achieve accurate positioning even in complex environments and meet the needs of industrial measurements.
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来源期刊
Journal of Electronic Imaging
Journal of Electronic Imaging 工程技术-成像科学与照相技术
CiteScore
1.70
自引率
27.30%
发文量
341
审稿时长
4.0 months
期刊介绍: The Journal of Electronic Imaging publishes peer-reviewed papers in all technology areas that make up the field of electronic imaging and are normally considered in the design, engineering, and applications of electronic imaging systems.
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