基于TMS320C6748的激光光斑中心快速精确定位的实现
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摘要
激光基准技术在位移检测系统中应用越来越多,激光光斑中心定位的速度和精确度直接决定了整个系统的工作性能。传统的激光光斑中心检测可以达到良好的精确度,但是求取速度存在一定的不足。因此提出一种基于图像金字塔的优化算法,只需遍历少量像素点便可定位出图像感兴趣区域,然后只针对图像感兴趣区域进行预处理,如此处理大幅提高了TMS320C6748的处理速度。通过实验测试,处理一帧激光图像的时间为12. 75 ms,检测精度可达到0. 1 mm,目前已将该算法成功应用于激光基准桥梁挠度检测系统中。
The laser datum technology is used more and more in the displacement detection system. The speed and precision of the laser spot center positioning directly determine the performance of the whole system.The traditional laser spot center detection can achieve high accuracy,but there is a certain deficiency in the acquisition speed. Therefore,an optimal algorithm based on image pyramid is proposed. Only a small number of pixels can be traversed to locate the image ROI,and then pre-process the image ROI which greatly improves the processing speed of the TMS320 C6748. Through the test,the time of processing one frame of laser image is 12. 75 ms,the detection precision can reach 0. 1 mm,and the algorithm is successfully applied to the detection system of bridge deflection based on laser datum.
The laser datum technology is used more and more in the displacement detection system. The speed and precision of the laser spot center positioning directly determine the performance of the whole system.The traditional laser spot center detection can achieve high accuracy,but there is a certain deficiency in the acquisition speed. Therefore,an optimal algorithm based on image pyramid is proposed. Only a small number of pixels can be traversed to locate the image ROI,and then pre-process the image ROI which greatly improves the processing speed of the TMS320 C6748. Through the test,the time of processing one frame of laser image is 12. 75 ms,the detection precision can reach 0. 1 mm,and the algorithm is successfully applied to the detection system of bridge deflection based on laser datum.
引文
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[2]钱寅泉,张学亮,袁桂芳.中小跨径桥梁挠度测试方法比较[J].中外公路,2012,32(2):89-92.
[3]雷俊卿.公路悬索桥检测评估与养护维修[J].中国公路,2017,3(21):87-89.
[4]张文会.嵌入式多点桥梁挠度监测系统研究与实现[D].重庆:重庆交通大学,2013.
[5]王会峰,张文革,王金娜.激光驾束制导仪光信息场模拟测试技术[J].激光与红外,2011,41(9):974-978.
[6]王会峰,冀芳,汪大宝.激光基准成像测量光斑图像的亚像素检测算法[J].量子电子报,2008,25(04):402-406.
[7]李亚楠,赵耀,林春雨,等.基于图像分割的金字塔Lucas-Kanade光流法提取深度信息[J].铁道学报,2015,37(1):63-68.
[8]李迎春,范有臣,杜永红,等.激光主动成像图像降噪方法[J].激光与红外,2011,(09):1036-1040.
[9]刘好龙,侯文,范亚龙,等.一种改进的激光光斑中心定位算法[J].计算机测量与控制,2014,22(1):139-141.
[10]余罗,刘洪英,许帅,等.一种快速精确的瞳孔和角膜反射光斑中心定位算法的研究[J].中国生物医学工程学报,2017,36(4):433-441.
[11]王丽丽,胡中文,季杭馨.基于高斯拟合的激光光斑中心定位算法[J].应用光学,2012,33(5):986-989.
[12]吴家勇,王平江,陈吉红,巫孟良.基于梯度重心法的线结构光中心亚像素提取方法[J].中国图象图形学报,2009,14(07):1354-1360.
[13] MIAO Zelang,SHI Wenzhong,ZHANG Hua,et al. Road Centerline Extraction From High-Resolution Imagery Based on Shape Features and Multivariate Adaptive Regression Splines[J]. IEEE Geoscience and Remote Sensing Letters,2013,10(3):583-587.
[14] ZHANG W,SUN L.M,SUN S. Bridge-Deflection Estimation through Inclinometer Data Considering Structural Damages[J]. Journal of Bridge Engineering,2017,22(2):564-569.
[15] ZHONG S. New entropic thresholding approach using graylevel spatial correlation histogram[J]. Optical Engineering,2010,49(12):1127-1134.
[16] WANG H,DONG Y. An improved image segmentation algorithm based on Otsu method[J]. Proceedings of SPIEThe International Society for Optical Engineering,2008,6625(6):289-292.
[17]赵琦,郝士琦,张岱.改进阈值分割的光斑中心定位方法[J].激光与红外,2018,48(05):633-637.
[18]陈和,杨志浩,郭磐,张寅超,陈思颖.激光光斑中心高精度定位算法研究[J].北京理工大学学报,2016,36(02):181-185.
[19]陈梦苇,杨应平,贾信庭,冷芬.四象限探测器光斑中心定位算法研究[J].武汉理工大学学报(交通科学与工程版),2013,37(05):1124-1127.
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