基于斜率关联度和Krisch算子的图像边缘检测

楚雄师范学院学报 ›› 2021, Vol. 36 ›› Issue (3): 1-7.

• 数学 • 下一篇

基于斜率关联度和Krisch算子的图像边缘检测

薛文格, 邝天福

楚雄师范学院数学与计算机科学学院,云南楚雄 675000

收稿日期:2020-11-28 出版日期:2021-05-20 发布日期:2021-07-23
作者简介:薛文格（1982–）,女,硕士,楚雄师范学院数学与计算机科学学院讲师,主要研究方向为模式识别与图像处理。E-mail： xwg@cxtc.edu.cn, Tel. 15808785801

Image Edge Detection Based on Slop Correlation Degree and Krisch Operator

XUE Wenge, KUANG Tianfu

College of Mathematics and Computer Science, Chuxiong Normal University, Chuxiong, Yunnan Province 675000

Received:2020-11-28 Online:2021-05-20 Published:2021-07-23

摘要/Abstract

摘要： 针对利用灰色关联分析方法检测图像边缘时存在边缘定位不准确、连续性较差的问题,结合斜率关联度和Krisch算子检测边缘的优点,提出了一种融合斜率关联度和Krisch算子的图像边缘检测算法。该算法首先将Krisch算子中八个方向模板分别作为斜率关联度的参考序列,然后利用斜率关联度方法计算出由图像中每个像素构成的比较序列与参考序列的关联度,并与给定的阈值比较,判别像素是否为边缘点。实验结果表明,基于斜率关联度和Krisch算子的图像边缘检测算法简单、易实现,检测出的边缘连续、清晰、定位准确、细节丰富,是一种有效的图像边缘检测算法。

关键词: 斜率关联度, Krisch算子, 边缘检测, 参考序列, 比较序列

Abstract: Aiming at the problems of inaccurate edge positioning and poor continuity when using the grey relational analysis method to detect image edges, combining the advantages of slop correlation degree and Krisch operator, this paper proposes an algorithm that combines slop correlation degree with Krisch operator. First make the eight direction templates of Krisch operator as reference sequence of slop correlation degree, then use slop correlation degree to calculate each pixel correlation degree of the reference sequence and comparison sequences and compare it with the given threshold value to distinguish whether the pixel is edge point. The experimental results show that this algorithm is simple and easy to implement and image edges detected are continuous and clear with accurate positioning and rich details. In short, it is an efficient image edge detection algorithm.

Key words: slop correlation degree, krisch operator, edge detection, reference sequence, comparison sequence

中图分类号:

O243

薛文格, 邝天福. 基于斜率关联度和Krisch算子的图像边缘检测[J]. 楚雄师范学院学报, 2021, 36(3): 1-7.

XUE Wenge, KUANG Tianfu. Image Edge Detection Based on Slop Correlation Degree and Krisch Operator[J]. Journal of Chuxiong Normal University, 2021, 36(3): 1-7.

参考文献

[1] 张红霞,王灿,刘鑫,等.图像边缘检测算法研究新进展[J].计算机工程与应用,2018,54(14):11–18.
Zhang H X, Wang C, Liu X, et al. Image edge detection algorithm and its new development[J]. Computer Engineering and Applications,2018,54(14):11–18.
[2] 邓聚龙. 灰理论基础[M].武汉:华中科技大学出版社,2002:12–30.
Deng J L.Grey Theory Basis [M]. Wuhan:Huazhong University of Science and Technology Press,2002:12–30.
[3] 马苗,樊养余,谢松云,等.基于灰色系统理论的图像边缘检测新算法[J].中国图像图形学报,2003,8(10):1136–1139.
Ma M, Fan Y Y, Xie S Y, et al. A novel algorithm of image edge detection based on gray system theory[J]. Journal of Image and Graphics, 2003,8(10):1136–1139.
[4] 冷欣,宋文龙.基于改进的灰色关联度的根系图像边缘检测[J].包装工程,2016,37(15):46–49.
Leng X, Song W L.Root image edge detection based on improved gray correlation degree[J]. Packaging Engineering, 2016, 37(15): 46–49.
[5] 张洪群,顾吟雪,郭擎.灰色关联分析与模糊推理边缘检测图像融合法[J].遥感信息,2020,35(1):15–27.
Zhang H Q, Gu Y X, Guo Q.Image fusion based on edge detection of grey relational analysis and fuzzy inference[J]. Remote Sensing Information,2020,35(1):15–27.
[6] 胡鹏,傅仲良,陈楠.利用灰色理论进行图像边缘检测[J].武汉大学学报(信息科学版),2006,31(5):411–413.
Hu P, Fu Z L, Chen N.Image edge detection based on gray system theory[J]. Geomatics and Information Science of Wuhan University,2006,31(5):411–413.
[7] 齐英剑,李青,吴正朋.基于灰色相对关联度的图像边缘检测算法[J].中国传媒大学学报(自然科学版),2010,17(3):46–49.
Qi Y J, Li Q, Wu Z P.An algorithm of image edge detection based on gray system theory[J]. Journal of Communication University of China (Science and Technology) , 2010, 17(3): 46–49.
[8] 郑子华,陈家祯,陈利永.基于灰色绝对关联度的边缘检测算法[J].福建师范大学学报(自然科学版),2004,20(4):20–23.
Zheng Z H, Chen J Z, Chen L Y.An algorithm of image edge detection based on gray correlation analysis[J]. Journal of Fujan Normal University (Natural Science Edition ) , 2004, 20(4):20–23.
[9] 王铁鹏. 基于灰色系统理论的图像边缘检测应用研究[D].西安:西安理工大学(硕士学位论文),2012.
Wang T P.Application research of image edge detection based on the grey system theory [D]. Xi'an:Xi'an University of Technology (Master Thesis), 2012.
[10] 周志刚,桑农,万立,等.利用灰色理论构造统计量进行图像边缘检测[J].系统工程与电子技术,2013,35(5):1110–1114.
Zhou Z G, Sang N, Wan L, et al. Statistic-based image edge detection about gray system theory[J]. Systems Engineering and Electronics, 2013, 35(5):1110–1114.
[11] 李东玥,徐龙春,张敏风,等.一种新的Kirsch边缘检测算法[J].中国医学物理学杂志,2017,34(7):686–689.
LiD Y, Xu L C, Zhang M F, et al. A novel Kirsch edge detection algorithm[J]. Chinese Journal of Medical Physics, 2017, 34(7)：686–689.
[12] 刘思峰,党耀国,方志耕,等.灰色系统理论及其应用[M].北京:科学出版社,2004:20–60.
Liu S F, Dang Y G, Fang Z G, et al.Grey System Theory and Application [M]. Beijing: Science Press, 2004:20–60.
[13] Fabrizio R, Annarita L.Color edge detection in presence of gaussian noise using nonlinear pretreatment[J]. IEEE Transactions on Instrumentation and Measurement, 2005, 54(1):352–358.
[14] 罗巍,陈曙东,龚立晨,等.基于深度学习的无人机遥感影像船只检测方法[J].船舶物资与市场,2019(4):25–28.
Luo W, Chen S D, Gong L C, et al. A method of drone remote sensing ship image detection based on deep learning[J]. Marine Equipment/Materials Marketing, 2019(4):25–28.
[15] 闫明艳,陈根铭,赖超,等.人工智能对肺结核患者病变检出及定性诊断价值研究[J].新发传染病电子杂志,2018,3(4):214–217.
Yan M Y, Chen G M, Lai C, et al. Clinical value of artificial intelligence in detecting and analyzing lesions in patients with pulmonary tuberculosis[J]. Electronic Journal of Emerging Infectious Diseases, 2018,3(4):214–217.
[16] 娄正良,刘昌平,白洪亮,等.汉字串的模糊匹配算法[J].微电子学与计算机,2004,21(4):13–24.
Lou Z L, Liu C P, Bai H L, et al. A fuzzy match algorithm of Chinese character strings[J]. Microelectronics and Computer, 2004, 21(4):13–24.

基于斜率关联度和Krisch算子的图像边缘检测

Image Edge Detection Based on Slop Correlation Degree and Krisch Operator

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价