基于分数阶微分的图像边缘细节检测与提取

doi:10.3969/j.issn.0372-2112.2013.10.001

电子学报 ›› 2013, Vol. 41 ›› Issue (10): 1873-1880.DOI: 10.3969/j.issn.0372-2112.2013.10.001

• 学术论文 • 下一篇

基于分数阶微分的图像边缘细节检测与提取

陈青^1,3, 刘金平^1,2, 唐朝晖¹, 李建奇¹, 吴敏¹

1. 中南大学信息科学与工程学院, 湖南长沙 410083;
2. 湖南师范大学数学与计算机科学学院, 湖南长沙 410081;
3. 湖南工业大学计算机与通信学院, 湖南株洲 412008

收稿日期:2013-01-21 修回日期:2013-08-01 出版日期:2013-10-25
- 通讯作者:
- 刘金平
- 作者简介:
- 陈青 女,1967年10月出生,湖南长沙人,湖南工业大学计算机与通信学院副教授.2004毕业于中南大学信息科学与工程学院,获硕士学位,现为中南大学信息科学与工程学院博士研究生.主要从事计算机信息技术、智能自动化信息检测与处理等领域的研究开发工作.
- 基金资助:
- 国家自然科学基金 (No.61071176,No.61171192,No.61272337; No.61134006)

Detection and Extraction of Image Edge Curves and Detailed Features Using Fractional Differentiation

CHEN Qing^1,3, LIU Jin-ping^1,2, TANG Zhao-hui¹, LI Jian-qi¹, WU Min¹

1. School of Information Science & Engineering, Central South University, Changsh, Hunan 410083, China;
2. College of Mathematics and Computer Science, Hunan Normal University, Changsha, Hunan 410081, China;
3. School of Computer and Communication, Hunan University of Technology, Zhuzhou, Hunan 412008, China

Received:2013-01-21 Revised:2013-08-01 Online:2013-10-25 Published:2013-10-25
- Supported by:
- National Natural Science Foundation of China (No.61071176, No.61171192, No.61272337, No.61134006)

摘要/Abstract

摘要： 图像边缘细节包含重要的视觉感知信息,是进一步进行图像理解与场景感知的基础.针对常用的边缘梯度检测方法难以有效提取类似于分形纹理结构的复杂图像边缘问题,提出一种基于分数阶微分的图像边缘检测方法.该方法首先基于分数阶微分的性质进行图像拐点检测,并进一步结合拉格朗日多项式插值和Grumwald-Letnikov(G-L)分数阶微分的定义,推导出具有非整数步长像素信息的图像边缘检测算子.实验表明,该方法能有效提取图像中的边缘细节(拐点)特征.对被噪声严重污染的具有复杂边缘细节的图像,该算子同样具有较好的边缘细节检测能力,获得更好的视觉效果.

关键词: 图像边缘细节检测, 图像拐点, 分数阶微分, 抗噪能力

Abstract: The edge details in images involve significant visual perception information,which play an important role in the further image understanding and scene perception.An image edge detection and extraction method is presented based on the fractional differentiation theory aiming at solving the problems of inaccurate edge detection like fractal structures in the images by the traditional edge detection methods.Firstly,the inflexion points in the images are detected based on the characteristics of fractional differentiation;then,an image edge detail detection and extraction operator with sub-pixel interpolation is derived from the Grumwald-Letnikov (G-L) definition of fractional differentiation combining with the Lagrange interpolation polynomials.The experimental results demonstrate that the proposed operator is capable of extracting image edge details (inflexion points) efficiently.Furthermore,it is able to detect the useful object edge details from image with serious noise to achieve better visual effect.

Key words: image edge detail detection, image flexion points, fractional differentiation, noise robustness

中图分类号:

TP391.4

陈青, 刘金平, 唐朝晖, 等. 基于分数阶微分的图像边缘细节检测与提取[J]. 电子学报, 2013, 41(10): 1873-1880.

CHEN Qing, LIU Jin-ping, TANG Zhao-hui, et al. Detection and Extraction of Image Edge Curves and Detailed Features Using Fractional Differentiation[J]. Acta Electronica Sinica, 2013, 41(10): 1873-1880.

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基于分数阶微分的图像边缘细节检测与提取

Detection and Extraction of Image Edge Curves and Detailed Features Using Fractional Differentiation

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