基于改进Harris算法的汉字图像角点检测

doi:10.3969/j.issn.1006-2475.2014.05.022

计算机与现代化 ›› 2014, Vol. 0 ›› Issue (5): 99-103,117.doi: 10.3969/j.issn.1006-2475.2014.05.022

基于改进Harris算法的汉字图像角点检测

塔里木大学信息工程学院,新疆阿拉尔843300

收稿日期:2014-02-25 出版日期:2014-05-28 发布日期:2014-05-30
作者简介:姚娜(1981-),女,山东聊城人,塔里木大学信息工程学院讲师,硕士,研究方向:图像识别,图像复原; 吕海芳(1986-),女,青海西宁人,助理实验师,本科,研究方向:计算机应用。
基金资助:
塔里木大学校长自然基金资助项目(TDZKSSZD201302)

Improved Harris Corner Detection for Chinese Characters Image

College of Information Engineering, Tarim University, Alaer 843300, China

Received:2014-02-25 Online:2014-05-28 Published:2014-05-30

摘要/Abstract

摘要： 根据汉字图像的特点，借鉴加速分割检测特征算法的思想，提出一种改进的Harris算法对汉字图像进行角点检测。首先，计算像素值初步判断出非角点并排除；然后，通过计算传统Harris算法中的角点响应函数对剩余的像素进行角点检测；最后，借鉴加速分割检测特征算法的思想对伪角点进行删除。最终检测出的角点是汉字笔画的起点和末端的角点，为下一步特征提取中确定线段的位置和计算线段的长度提供有利的技术基础。通过对一定数量的汉字图像的实验仿真，将本文方法与几种常用的角点检测方法进行比较，本文方法在检测正确率方面有所提高，但在运行时间上没有达到最短，综合考虑正确率和运行时间，本文方法较其他几种方法有所提高。
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关键词: 角点检测, 汉字图像, Harris算法

Abstract:

According to characteristics of Chinese characters image, we proposed an improved corner detection method based on Harris algorithm， and the ideal of FAST to improve detection rate for next feature extraction. Firstly, the pixels were computed to remove non-corners, and then the image of Chinese characters was detected for corners using Harris algorithm. Secondly, FAST for reference was used and the false corners were removed. The corners found lastly were endpoints of line segments, providing the length of line segments for shape feature extraction. The proposed method was compared with several corner detection methods over a number of images. Experimental results show that the proposed method is better in terms of detection rate, but not best for running time.
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Key words: corner detection, Chinese characters image, Harris algorithm

中图分类号:

TP391

姚娜,吕海芳,白铁成. 基于改进Harris算法的汉字图像角点检测[J]. 计算机与现代化, 2014, 0(5): 99-103,117.

YAO Na, LYU Hai-fang, BAI Tie-cheng. Improved Harris Corner Detection for Chinese Characters Image[J]. Computer and Modernization, 2014, 0(5): 99-103,117.

参考文献

［1］ Moravec H P. Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover［D］. Pennsylvania: Carnegie-Mellon University, 1980.
［2］ Harris C, Stephens M. A combined corner and edge detector［C］// Proceedings of the 4th Alvey Vision Conference. 1988:147-151.
［3］ Noble Julia Alison. Descriptions of Image Surfaces［D］. Oxford: Oxford University, 1989.
［4］ Schmid C, Mohrand R, Bauckhage C. Evaluation of interest point detectors［J］. International Journal of Computer Vision, 2000,37(2):151-172.［5］ Shi J, Tomasi C. Good features to track［C］// Proceedings of 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1994:593-600.
［6］ Smith S M, Brady J M. SUSAN：A new approach to low level image processing［J］. International Journal of Computer Vision, 1997,23(1):45-78.
［7］ He X C, Yung N H C. Curvature scale space corner detector with adaptive threshold and synamic region of support［C］// Proceedings of the 17th International Conference on Pattern Recognition. 2004,2:791-794.
［8］ Rosten E, Drummond T. Fusing points and lines for high performance tracking［C］// Proceedings of the 10th IEEE International Conference on Computer Vision. 2005,2:1508-1515.
［9］ Rosten E, Drummond T. Machine learning for high-speed corner detection［C］// Proceedings of the 9th European Conference on Computer Vision. 2006:430-443.
［10］Rosten E, Porter R, Drummond T. Faster and better: A machine learning approach to corner detection［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010,32(1):105-119.
［11］王民钢,王超,樊英平,等. 基于Harris的角点检测改进算法［J］. 计算机仿真， 2012,29(11):294-298.
［12］王万良,金亦挺,赵燕伟,等. 点到弦距离累加的自适应角点检测［J］. 中国图象图形学报， 2012,17(12):1500-1508.
［13］匡智奇,粱春红. 手掌角点检测及掌纹区域确定的新方法［J］. 计算机与现代化, 2012(9):123-126.
［14］马丽红,谭幸均. 迭代分割逼近:新的基于局部响应显著度的角点检测［J］. 中国图象图形学报， 2012,17(3):402-411.
［15］周龙萍. 基于改进的Harris算法检测角点［J］. 计算机技术与发展， 2013,23(2):11-14.
［16］高晶,吴育峰,吴昆,等. 基于角点检测的图像匹配算法［J］. 仪器仪表学报， 2013,34(8):1717-1725.
［17］李枫,程小燕. 基于提升小波和Harris角点检测的版权认证算法［J］. 太原师范学院学报:自然科学版, 2013,12(3):85-88.

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基于改进Harris算法的汉字图像角点检测

Improved Harris Corner Detection for Chinese Characters Image

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