Polygon Detection Based on Meta-representation
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摘要: 特征检测是图像处理的经典问题,但多边形检测一直研究较少,针对这一现况,提出了一种简单有效的多边形检测方法——基于基元表示的多边形检测方法. 该方法的主要思想是:首先,检测图像关键点并计算关键点附近的边缘方向,利用关键点位置与边缘方向信息定义点基元(一维基元);其次,将满足组合条件的点基元进行组合, 获得线基元(二维基元);然后,将满足组合条件的线基元与点基元进行组合,获得三维基元或者三角形,实现三角形检测;同样,可将满足组合条件的n(n≥2)维基元与点基元进行组合,获得n+1维基元或者n+1边形,实现多边形检测. 实验结果表明,本文提出的基于基元表示的多边形检测方法可准确有效地检测出图像中包含的各种多边形. 此外,本文提出的基元表示方法也为其他由线条组成的复杂图形的检测提供了一种新的思路.Abstract: Feature detection is one of the classic topics in the field of image processing; however, only little research has been made on polygon detection problem. Focusing on this problem, this paper presents a simple and effective method for polygon detection, called polygon detection method based on meta-representation. The main idea of this method is as follows: firstly, the key-points and their local edge directions are detected, and point metas (1-D metas) can be defined using the position and direction information of the key-points; then, line metas (2-D metas) can be attained by combining any two point metas that satisfy the constraint conditions; thirdly, a line meta and a point meta which satisfy the constraint conditions can be combined into a 3-D meta or triangle, and thus triangle detection is achieved. Similarly, considering an n-D meta (n≥ 2) and a point meta satisfying the constraint conditions, (n+1)-D meta or n+1 sided polygon can be constructed, and thus polygon detection is achieved. Experiments show that the polygon detection method based on meta-representation can perform effectively and accurately for polygon detection. Besides, the meta-representation method proposed in this paper can provide an idea for detecting other graphics consist of line segments.
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Key words:
- Meta-representation /
- point meta /
- line meta /
- polygon detection
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[1] Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, 60(2): 91-110[2] Mikolajczyk K, Schmid C. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis Machine Intelligence, 2005, 27(10): 1615-1630[3] Mikolajczyk K, Tuytelaars T, Schmid C, Zisserman A, Matas J, Schaffalitzky F, Kadir F, Gool L V. A comparison of affine region detectors. International Journal of Computer Vision, 2005, 65(1-2): 43-72[4] Yang Dan, Wang Hong-Xing, Zhang Xiao-Hong, Yan Wei-Jie. LoG transform of contour curves and detection of image covariant regions. Acta Automatica Sinica, 2010, 36(6): 817-822(杨丹, 王洪星, 张小洪, 阎卫杰. 轮廓曲线的LoG变换及图像共变区域的检测. 自动化学报, 2010, 36(6): 817-822)[5] Davies E R. Machine Vision: Theory, Algorithms, Practicalities (Third Edition). San Francisco: Elsevier, 2005. 387-410[6] Laha A, Sen A, Sinha B P. Parallel algorithms for identifying convex and non-convex basis polygons in an image. Parallel Computing, 2005, 31(3-4): 290-310[7] Barnes N, Loy G, Shaw D. The regular polygon detector. Pattern Recognition, 2010, 43(3): 592-602[8] Barnes N, Loy G, Shaw D, Robles-Kelly A. Regular polygon detection. In: Proceedings of the 10th IEEE International Conference on Computer Vision. Beijing, China: IEEE, 2005. 778-785[9] Barnes N, Loy G. Real-time regular polygonal sign detection. In: Proceedings of the 5th International Conference on Field and Service Robotics. Berlin, Germany: Springer, 2005. 55-66[10] Manay S, Paglierone D W. Matching flexible polygons to fields of corners extracted from images. Lecture Notes in Computer Science. Berlin: Springer, 2007. 447-459[11] Shi Jun, Xiao Zhi-Heng, Chang Qian. An algorithm for recognizing geometrical shapes automatically based on tunable filter. Journal of North University of China (Natural Science), 2009, 30(5): 467-471(施俊, 肖至恒, 常谦. 基于可调滤波器的几何图形自动识别算法研究. 中北大学学报(自然科学版), 2009, 30(5): 467-471)[12] Croitoru A, Doytsher Y. Right-angle rooftop polygon extraction in regularized urban areas: cutting the corners. The Photogrammetric Record, 2004, 19(108): 311-341[13] Gates J W, Haseyama M, Kitajima H. Real-time polygon extraction from complex images. In: Proceedings of the IEEE International Symposium on Circuits and Systems. Geneva, Switzerland: IEEE, 2000. 309-312[14] Croitoru A, Doytsher Y. Right-angle rooftop polygon extraction in regularized urban areas: cutting the corners. The Photogrammetric Record, 2004, 19(108): 311-341[15] Harris C, Stephens M J. A combined corner and edge detector. In: Proceedings of the 4th Alvey Vision Conference. Berlin, Germany: Springer, 1988. 147-152[16] Kathe U. Integrated edge and junction detection with the boundary tensor. In: Proceedings of the 9th IEEE International Conference on Computer Vision. Nice, France: IEEE, 2003. 424-431[17] Mokhtarian F, Suomela R. Robust image corner detection through curvature scale space. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(12): 1376-1381[18] Mokhtarian F, Mackworth A K. A theory of multi-scale, curvature-based shape representation for planar curves. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(8): 789-805[19] Zhang Lei, Zhang Zhi-Sheng, Shi Jin-Fei, Fu Qing-Shan. A new algorithm for fast corner detection using line search mechanism. Acta Automatica Sinica, 2010, 36(4): 509-521(张磊, 张志胜, 史金飞, 付清山. 一种快速检测图像角点特征的线搜索式方法. 自动化学报, 2010, 36(4): 509-521)[20] Wang Yu-Zhu, Yang Dan, Zhang Xiao-Hong. Robust corner detection based on multi-scale curvature product in B-spline scale space. Acta Automatica Sinica, 2007, 33(4): 414-417[21] Ruzon M A, Tomasi C. Edge, junction, and corner detection using color distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(11): 1281-1295[22] Deschenes F, Ziou D. Detection of line junctions in gray-level images. In: Proceedings of the 15th International Conference on Pattern Recognition. Barcelona, Spain: IEEE, 2000. 754-757[23] Lai K K, Wu P S Y. Effective edge-corner detection method for defected images. In: Proceedings of the 3rd International Conference on Signal Processing. Beijing, China: IEEE, 1996. 1151-1154[24] Kohlmann K. Corner detection in natural images based on the 2-D Hilbert transform. Signal Processing, 1996, 48(3): 225-234[25] Wang Zhi-Heng, Wu Fu-Chao, Wang Xu-Guang. Corner detection and sub-pixel localization based on local orientation distribution. Journal of Software, 2008, 19(11): 2932-2942(王志衡, 吴福朝, 王旭光. 基于局部方向分布的角点检测及亚像素定位. 软件学报, 2008, 19(11): 2932-2942)
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