A Systemic Algorithm of Elliptical Artificial Targets Identification and Tracking for Image Sequences from Videogrammetry

doi:10.11947/j.AGCS.2015.20130452

Abstract

Abstract:

In order to satisfy the requirement of identification and tracking the elliptical artificial targets fast and accurately for the image sequences from videogrammetric measurement for structural health monitoring, this paper proposes a systemic algorithm to identify and track the elliptical targets using the image block technique. The proposed method extracts the image block from original images to reduce the amount of data processing for the oval targets tracking. The mathematical morphology and elliptical geometric characteristics are integrated to eliminate the non-elliptical edge information to extract the elliptical contour in the range of image block. At last, the sub-pixel center location for elliptical artificial targets is acquired by the least square algorithm. The experimental results show that RMS error of 0.025 pixel can be achieved by the proposed method, furthermore, compared with the random Hough transform and template recognition algorithm, the tracking efficiency is improved over 5 times.

Key words: videogrammetric measurement, image block, ellipse identification, mathematical morphology, least square algorithm

CLC Number:

P232

LIU Xianglei, TONG Xiaohua, MA Jing. A Systemic Algorithm of Elliptical Artificial Targets Identification and Tracking for Image Sequences from Videogrammetry[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6): 663-669.

References

[1] HILLEBRAND M,STEVANOVIC N,HOSTICKA B J,et al. High Speed Camera System Using a CMOS Image Sensor[C]//Proceedings of the IEEE Intelligent Vehicles Symposium. Dearborn:IEEE,2000:656-661.
[2] MUEHLMANN U,RIBO M,LANG P,et al.A New High Speed CMOS Camera for Real-time Tracking Applications[C]//Proceedings of the 2004 IEEE International Conference on Robotics and Automation. New Orleans:IEEE,2004,5:5195-5200.
[3] REMONDINO F.Videogrammetry for Human Movement Analysis[C]//Proceedings of the 9th International Symposium on 3D Analysis of Human Movement. Zurich:Institute of Geodesy and Photogrammetry, 2006:25-33.
[4] WANG J B,ZHANG Y,YANG M G,et al.Observation of Arc Discharging Process of Nanocomposite Ag-SnO₂ and La-doped Ag-SnO₂ Contact with A High-speed Camera[J].Materials Science and Engineering:B,2006,131(1-3):230-234.
[5] FRASER C S,RIEDEL B.Monitoring the Thermal Deformation of Steel Beams via Vision Metrology[J].ISPRS Journal of Photogrammetry and Remote Sensing,2000,55(4):268-276.
[6] LEIFER J,WEEMS B J,KIENLE S C,et al.Three-dimensional Acceleration Measurement Using Videogrammetry Tracking Data[J].Experimental Mechanics,2011,51(2):199-217.
[7] FU G K,MOOSA A G.An Optical Approach to Structural Displacement Measurement and Its Application[J].Journal of Engineering Mechanics,2002,128(5):511-520.
[8] LEE J J, FUKUDA Y, SHINOZUKA M, et al.Development and Application of A Vision-based Displacement Measurement System for Structural Health Monitoring of Civil Structures[J].Smart Structures and Systems, 2007, 3(3):373-384.
[9] LIN S Y,MILLS J P,GOSLING P D.Videogrammetric Monitoring of As-built Membrane Roof Structures[J].The Photogrammetric Record,2008,23(122):128-147.
[10] YAN Bei,WANG Bin,LI Yuan.Optimal Ellipse Fitting Method Based on Least-square Principle[J].Journal of Beijing University of Aeronautics and Astronautics,2008,34(3):295-298.(闫蓓,王斌,李媛.基于最小二乘法的椭圆拟合改进算法[J].北京航空航天大学学报,2008,34(3):295-298.)
[11] LIU Shenghao,ZENG Libo,WU Qiongshui,et al. A Novel Cervical Cell Segmentation Method Based on Ellipse Deformable Template Technology[J].Chinese Journal of Scientific Instrument,2004,25(2):222-225.(刘生浩,曾立波,吴琼水,等.一种基于椭圆可变形模板技术的宫颈细胞图像分割方法[J].仪器仪表学报,2004,25(2):222-225.)
[12] HOUGH V,PAUL C.Method and Means for Recognizing Complex Patterns:US,069654[P/OL].1962-12-18.
[13] NIU X, HU Z,YANG S.Hierarchical Ellipse Detection Algorithm Based on Local PCA Hough Transform with Parameter Restraint[J].Journal of Computer Applications, 2009, 29(5):1365-1368.
[14] ZHOU T H,PAPANIKOLOPOULOS N.Enhancing the Randomized Hough Transform with k-means Clustering to Detect Mutually-Occluded Ellipses[C]//Proceedings of the 19th Mediterranean Conference on Control & Automation. Corfu:IEEE,2011:327-332.
[15] LIU R,SUN H M,WEI J,et al.Ellipse Detection and Fitting Based on RANSAC[J].Journal of Beijing Institute of Clothing Technology:Natural Science Edition, 2012,32(4):74-78.
[16] DOHI K,HATANAKA Y,NEGI K.Deep-pipelined FPGA Implementation of Ellipse Estimation for Eye Tracking[C]//Proceedings of the 22nd International Conference on Field Programmable Logic and Application.Oslo:IEEE,2012:458-463.
[17] LI Chang, Researching on Key Technique for 3D Auto-Reconstruction of City Street Elevation[J]. Acta Geodaetica et Cartographic Sinica, 2011, 40(2): 268-268.(李畅. 城市街道立面自动重建关键技术研究[J]. 测绘学报, 2011, 40(2): 268-268.)
[18] XUE Ting,SUN Mei,ZHANG Tao,et al.Complete Approach to Automatic Identification and Sub-pixel Center Location for Ellipse Feature[J].Journal of Optoelectronics·Laser,2008,19(8):1076-1078.(薛婷,孙梅,张涛,等. 类椭圆特征自动识别及亚像素提取的完整实现[J].光电子·激光,2008,19(8):1076-1078.)
[19] QIAO Y,ONG S H.Arc-based Evaluation and Detection of Ellipse[J].Pattern Recognition,2007,40(7):1990-2003.
[20] LI Liangfu,FENG Zuren,HE Kailiang.An Improved Algorithm for Ellipses Detection Based on Randomized Hough Transform[J].Pattern Recognition and Artificial Intelligence,2005,18(4):459-464.(李良福,冯祖仁,贺凯良.一种基于随机Hough变换的椭圆检测算法研究[J]. 模式识别与人工智能.2005,18(4):459-464.)
[21] PANG Yongjie,LIU Wei.Improved K-RANSAC Method for Ellipse Detection[J].Journal of Harbin Engineering University,2003,24(5):487-490.(庞永杰,刘维. 改进的K-RANSAC椭圆检测方法[J].哈尔滨工程大学学报,2003,24(5):487-490.)
[22] XIA Fei, ZHU Qianghua, JIN Guoqing. Accelerating RNA Secondary Structure Prediction Application Based on CPU+GPU Hybrid Platform[J]. Journal of National University of Defense Technology, 2013, 35(6):138-146. (夏飞,朱强华,金国庆.基于CPU+GPU混合计算平台的 RNA二级结构预测算法并行化研究[J]. 国防科技大学学报,2013,35(6):138-146.)
[23] QU Y D,CUI C S,CHEN S B,et al.A Fast Sub-pixel Edge Detection Method Using Sobel-zernike Moments Operator[J].Image and Vision Computing,2005,23(1):11 -17.
[24] FANG Liuyang, WANG Mi, LI Deren. A CPU-GPU Co-processing Orthographic Rectification Approach for Optical Satellite Imagery[J], Acta Geodaetica et Cartographic Sinica,2013, 42(5): 668-675. (方留杨,王密,李德仁.基于CPU和GPU协同处理的光学卫星遥感影像正射校正方法[J]. 测绘学报, 2013, 42(5): 668-675.)
[25] KANG Xiaochen, LIU Jiping, LIN Xiangguo. Parallel Filter of Progressive TIN Densification for Airborne LiDAR Point Clouds Using Multi-core CPU[J], Acta Geodaetica et Cartographic Sinica,2013, 42(3): 331-336. (亢晓琛,刘纪平,林祥国.基于多核CPU的机载LiDAR点云并行三角网渐进加密滤波方法[J]. 测绘学报, 2013, 42(3): 331-336.)