应用弦切变换提取几何特征实现目标检测

何 莲; 张启衡

doi:10.3788/OPE.20101808.1904

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应用弦切变换提取几何特征实现目标检测

信息科学 | 更新时间：2020-08-12

- 应用弦切变换提取几何特征实现目标检测
- Object detection based on geometric feature extracted by chord-tangent transformation
- 光学精密工程 2010年18卷第8期页码：1904-1913
- 作者机构：
  
  1. 中国科学院光电技术研究所,四川成都,610209
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
  
  中国科学院科技创新基金资助项目(No.A08K001)()
- DOI：10.3788/OPE.20101808.1904
  中图分类号： TP317.4
- 收稿日期：2009-08-27，
  
  修回日期：2009-10-09，
  
  网络出版日期：2010-08-20，
  
  纸质出版日期：2010-08-20
- 稿件说明：
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何莲, 张启衡. 应用弦切变换提取几何特征实现目标检测[J]. 光学精密工程, 2010,18(8): 1904-1913

HE Lian, ZHANG Qi-heng. Object detection based on geometric feature extracted by chord-tangent transformation[J]. 光学精密工程, 2010,18(8): 1904-1913
何莲, 张启衡. 应用弦切变换提取几何特征实现目标检测[J]. 光学精密工程, 2010,18(8): 1904-1913 DOI： 10.3788/OPE.20101808.1904.

HE Lian, ZHANG Qi-heng. Object detection based on geometric feature extracted by chord-tangent transformation[J]. 光学精密工程, 2010,18(8): 1904-1913 DOI： 10.3788/OPE.20101808.1904.

摘要

提出了应用弦切变换(CTT)来提取目标几何形状特征的方法

并基于对提取形状特征的匹配实现了对二维目标的检测。介绍了弦切变换的理论依据和算法的实现过程

同时进行了误差及可靠性分析。分析和实验表明

由于CTT可基于边缘点信息提取出更有意义的几何形状特征

这种几何特征不但具有平移、旋转和缩放的不变性

同时还可以输出目标相对于模板的旋转角度、缩放尺度等运动参数信息

因此

该方法在一定程度上克服了传统方法中灰度特征易受复杂环境和光照变化等影响的缺点

同时该特征对于目标边缘的部分失真或缺损也具有一定的鲁棒性。最后

对多组复杂环境下的图像序列进行了仿真实验

实验结果显示

检测的平均成功率达90%以上

而且在目标缺失或变形达到40%时

仍能得到比较准确的检测结果

这些结论验证了该方法的有效性。

Abstract

A method to extract the geometric features of planar objects was proposed by using the Chord-tangent Transformation (CTT)

then a 2D object was detected based on matching the geometric features obtained by the CTT. The theoretical basis of the CTT was introduced and how to realize the method was described. Meanwhile

the errors and reliability of the method were analyzed and discussed. It was pointed out that the CTT can extract a kind of senior geometric feature from the information of edge points

and the extracted geometric feature not only has invariant characters for translation

rotation and scale

but also can obtain some important parameters such as rotation angles and movement levels. Therefore

this method solves many problems caused by the unsteadiness of gray features in complex environments and changing illumination. Moreover

it shows a robustness for the condition that there is distortion or damage in the object edges. Finally

an experiment was undertaken with some image sequences from various complex conditions

and the results show that the average accuracy of object detection is over 90%. Even if the distortion or damage of the object edges has been more than 40%

it also can offer a more accurate detection result. These results prove the effectiveness and accuracy of method.

关键词

Keywords

references

DUBUSION M P, JAIN A K. A modified hausdorff distance for object matching . Processing of the 12th International Conference on Pattern Recognition, 1994: 566-568.

Ballard D H. Generalizing the hough transform to detect arbitrary shapes [J]. Pattern Recognition, 1981,13:111-122.

叶州海, 陈福民. 一种广义霍夫变换的改进[J]. 微型电脑应用, 2006,22(6):23-25.

YE ZH H, CHEN F M. An improving generalized hough transform[J]. Microcomputer Applications, 2006,22:23-25. (in Chinese)

吴刚,武春风,侯晴宇,等. 基于不变矩特征匹配的目标定位方法[J]. 光学精密工程, 2009,17(2):460-468.

WU G, WU CH F, HOU Q Y, et al.. Target location method based on invariable moment feature matching [J]. Opt. Precision Eng., 2009,22(6):460-468. (in Chinese)

FLUSSER J, SUK T. Pattern recognition by affine moment invariants [J]. Pattern Recognition, 1993,26:167-174.

ZAHN C T, ROSKIES R Z. Fourier descriptors for plane closed curves [J]. IEEE Trans on Computers, 1972,21:269-281.

SELVAGE J E, CHENOWETH D L, GOLD V E. Geometric feature extraction using the chord transformation . Proceedings of Aerospace Applications Conference, 1996,4:399-405.

MOORE D J H. An approach to the analysis and extraction of pattern features using integral geometry [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1972,8:97-102.

AYACHE N, FAUGERAS O D. HYPER: A new approach for the recognition and positioning of two-dimensional objects [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986,8:44-54.

DUFRESNE T E, DHAWAN A P. Chord-tangent transformation for object recognition [J]. Pattern Recognition, 1995,28:1321-1332.

吴莹莹,刘桥. 新颖的物体轮廓提取:基于双边滤波的多级边缘检测[J]. 计算机应用研究,2002,24(12):396-398.

WU Y Y, LIU Q. Novel object contour extraction: multi-scale edge detection based on bilateral filtering[J]. Application Research of Computers, 2002,24:396-398. (in chinese)

TOMASI C, MANDUCHI R. Bilateral filtering for gray and color images . Proc of the 6th International Conference on Computer Vision, 1998:839-846.

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