基于模板识别的高精度自动定位系统

刘荣; 彭艳敏; 唐粲; 毛建

基于模板识别的高精度自动定位系统

刘荣¹,
彭艳敏²,
唐粲³,
毛建⁴

1.
北京航空航天大学, 机械工程及自动化学院, 北京 100191
2. 天津医科大学, 医学影像学院, 天津 300203
3. 昆山市工业技术研究院, 昆山 215300
4. 中国电子科技集团, 第26研究所, 重庆 400060

基金项目: 江苏省科技项目(BE2009078)

详细信息

中图分类号: TP391
计量
- 文章访问数: 2684
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- 被引次数: 3
出版历程
- 收稿日期: 2011-03-12
- 网络出版日期: 2012-06-30

High-accuracy automatic locating system based on templates

1.
School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
2. School of Medical Imaging, Tianjin Medical University, Tianjin 300203, China
3. Kunshan Industrial Technology Research Institute, Kunshan 215300, China
4. The 26th Research Institute, China Electronics Technology Group Corporation, Chongqing 400060, China

摘要

摘要: 为满足机器人辅助医疗手术中高精度自动识别物体的需要,利用Bumblebee 2 摄像头拍摄图像,把黑白交互的椭圆和圆作为一个模板,用改进的角点提取方法提取出图像中的角点;在对图像进行增强之后,利用模板黑白格的几何对称性特征提取模板中的角点,然后区分出椭圆中的角点和圆中的角点,最后利用向量垂直关系提取出椭圆中的目标角点,识别出模板.通过Bumblebee 2自带的深度函数,提取模板的深度,得到模板在摄像头空间中的坐标,达到高精度自动定位物体的目的,克服传统摄像机需要标定内外参数的步骤.实验表明,定位误差在0.42 mm之内,基本上可以满足手术的要求.
- 角点 /
- 黑白格模板 /
- 机器人辅助手术 /
- Bumblebee 2摄像头
Abstract: In order to meet the requirement of robot assisted surgery which identified the object automatically with high precision, the Bumblebee 2 camera systems were used, and the ellipse and the circle were regarded as a template. The corners in the image were detected by the proposed algorithm. After the image enhanced for improving the contrast, using the symmetric properties of the black block and white block in the templates, the corners in the ellipse and in the circle were detected. At last using the vector vertical relationship, the goal vertex in the ellipse was extracted, and then the template was identified. Through the depth function of the Bumblebee 2, the world position of the templates was obtained automatically with the high accuracy. The system overcame the problem that the traditional cameras calibrated the inside and outside parameters. Finally, experiments show that the positioning accuracy will reach to 0.42 mm, which is satisfactory to the requirement of the surgery.
- corners /
- template /
- robot assisted surgery /
- Bumblebee 2 camera

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参考文献(12)

[1]	Ha Jongeun.Automatic detection of chessboard and its applications[J].Optical engineering,2009,48(6):067205
[2]	Maier H L M,Franz A,Meinzer H P,et al.Comparative assessment of optical tracking systems for soft tissue navigation with fiducial needles //Proceedings of SPIE,Medical Imaging.Bellingham:SPIE,2008:69181z
[3]	Wiles A D,Thompsona D G,Frantz D D.Accuracy assessment and interpretation for optical tracking system //Proceedings of SPIE,Medical Imaging.Bellingham:SPIE,2004:421-432
[4]	Arturo dela Escalera,Jose María Armingol.Automatic chessboard detection for intrinsic and extrinsic camera parameter calibration[J].Sensors,2010,10(3):2027-2044
[5]	Van de Weijer J,Gevers T,Geusebroek J M.Edge and corner detection by photometric quasi-invariants[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(4): 625-630
[6]	Zhu Qingsheng,Wang Yanxia,Liu Huijun.Auto-corner detection based on the eigenvalues product of covariance matrices over multi-regions of support[J].Journal of Software,2010,5(8):907-914
[7]	Tsai D M,Hou H T,Su H J.Boundary-based corner detection using eigenvalues of covariance matrices[J].Journal Pattern Recognition Letters,1999,20(1):31-40
[8]	胡海峰,熊银根.一种基于两次Radon变换检测棋盘格方格点的新算法[J].中山大学学报:自然科学版,2003,42(2):23-26 Hu Haifeng,Xiong Yingen.A new algorithm for chessboard grid corners detection based on two successive Radon transform[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2003,42(2):23-26(in Chinese)
[9]	Beaudet P R.Rotationally invariant image operators //International Joint Conference on Pattern Recognition.New York,NY:IEEE,1979,1:579-583
[10]	Lowe D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110
[11]	Harris C,Stephens M.A combined corner and edge detector //Proceeding of the Fourth Alvey Vision Conference.Manchester:The University of Sheffield Printing Unit,1988: 147-151
[12]	赵景秀,韩君君,王菁,等.一种改进的LoG图像边缘检测方法[J].计算技术与自动化,2009,28(3):74-77 Zhao Jingxiu,Han Junjun,Wang Jing,et al.An improved LoG image edge detection method[J].Computing Technology and Automation,2009,28(3):74-77(in Chinese)