|Table of Contents|

[1] He Kunxian, Wang Qing, Xiao Yanchang, Wang Xiaobing, et al. Image edge detection based on nonsubsampledcontourlet transform and mathematical morphology [J]. Journal of Southeast University (English Edition), 2012, 28 (4): 445-450. [doi:10.3969/j.issn.1003-7985.2012.04.013]
Copy

Image edge detection based on nonsubsampledcontourlet transform and mathematical morphology()
基于非下采样轮廓波变换与数学形态学方法的图像边缘检测
Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
28
Issue:
2012 4
Page:
445-450
Research Field:
Computer Science and Engineering
Publishing date:
2012-12-30

Info

Title:
Image edge detection based on nonsubsampledcontourlet transform and mathematical morphology
基于非下采样轮廓波变换与数学形态学方法的图像边缘检测
Author(s):
He Kunxian1, Wang Qing1, Xiao Yanchang1, Wang Xiaobing2
1 School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
2 Firing Office, Nanjing Artillery Academy, Nanjing 211132, China
何坤贤1, 王庆1, 肖彦昌1, 王晓兵2
1 东南大学仪器科学与工程学院, 南京210096; 2 南京炮兵学院射击教研室, 南京211132
Keywords:
image edge detection;  nonsubsampled contourlet transform(NSCT);  modulus maxima;  dual-threshold;  mathematical morphology;  structural elements
图像边缘检测;  非下采样轮廓波变换;  模极大值;  双阈值;  数学形态学;  结构元素
PACS:
TP391.41
DOI:
10.3969/j.issn.1003-7985.2012.04.013
Abstract:
A novel algorithm for image edge detection is presented. This algorithm combines the nonsubsampled contourlet transform and the mathematical morphology. First, the source image is decomposed by the nonsubsampled contourlet transform into multi-scale and multi-directional sub-bands. Then the edges in the high-frequency and low-frequency sub-bands are respectively extracted by the dual-threshold modulus maxima method and the mathematical morphology operator. Finally, the edges from the high-frequency and low-frequency sub-bands are integrated to the edges of the source image, which are refined, and isolated points are excluded to achieve the edges of the source image. The simulation results show that the proposed algorithm can effectively suppress noise, eliminate pseudo-edges and overcome the adverse effects caused by uneven illumination to a certain extent. Compared with the traditional methods such as LoG, Sobel, and Canny operators and the modulus maxima algorithm, the proposed method can maintain sufficient positioning accuracy and edge details, and it can also make an improvement in the completeness, smoothness and clearness of the outline.
提出了一种新的图像边缘检测算法, 该算法融合了非下采样轮廓波变换与数学形态学方法来实现图像的边缘检测.首先, 源图像被非下采样轮廓波变换分解成多尺度、多方向子带;然后, 分别采用双阈值模极大值算法和数学形态学方法提取高频与低频子带的边缘信息;最后, 综合高频、低频子带边缘信息, 得到源图像全部的边缘信息, 并进行细化, 剔除孤立点, 获得源图像的边缘.仿真实验结果表明:新算法能够有效抑制噪声, 去除伪边缘, 一定程度上克服了光照不均引起的不良影响;与传统经典算法LoG, Sobel和Canny及模极大值方法相比, 该算法能保持足够的定位精度和边缘细节, 且边缘轮廓的完整性、光滑度、清晰度等得到明显提升.

References:

[1] Mallat S, Zhong Sifen. Characterization of signals from multiscale edges[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(7): 710-732.
[2] Tao Hongjiu, Liu Jian, Tian Jinwen. Remote sense image edge detection based on wavelet transform and mathematical morphology [J]. Infrared and Laser Engineering, 2002, 31(2): 154-157.(in Chinese)
[3] Haralick R M, Sternberg S R, Zhuang Xinhua. Image analysis using mathematical morphology[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, 9(4): 532-550.
[4] Zhao Yuqian, Gui Weihua, Chen Zhencheng. Edge detection based on multi-structure elements morphology[C]//Proceedings of the 6th World Congress on Intelligent Control and Automation. Dalian, China, 2006: 9795-9798.
[5] Huang Hailong, Wang Hong, Guo Fan, et al. A multi-shape and multi-scale edge detection algorithm based on mathematical morphology [J]. Journal of Northeastern University: Natural Science, 2010, 31(10): 1483-1486.(in Chinese)
[6] Zhang Y T, Yin Z K, Wang J Y. A new image edge detection scheme [J]. Journal of Electronics & Information Technology, 2008, 30(6): 1295-1299.(in Chinese)
[7] Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation[J]. IEEE Transactions on Image Processing, 2005, 14(12): 2091-2106.
[8] Da Cunha A L, Zhou Jianping, Do M N. Nonsubsampled contourlet transform: filter design and applications in denoising[C]//Proc of the IEEE International Conference on Image Processing. Genova, Italy, 2005:1749-1752.
[9] Da Cunha A L, Zhou Jianping, Do M N. The nonsubsampled contourlet transform: theory, design, and application[J]. IEEE Transactions on Image Processing, 2006, 15(10): 3089-3101.
[10] Xiao Yihan, Xi Zhihong, Hai Tao, et al. Image edge detection based on nonsubsampled contourlet transform [J]. Systems Engineering and Electronics, 2011, 33(7): 1668-1672.(in Chinese)

Memo

Memo:
Biographies: He Kunxian(1979—), male, graduate; Wang Qing(corresponding author), male, doctor, professor, 3398a@263.net.
Foundation items: The National Key Technologies R& D Program during the 12th Five-Year Period of China(No.2012BAJ23B02), Science and Technology Support Program of Jiangsu Province(No.BE2010606).
Citation: He Kunxian, Wang Qing, Xiao Yanchang, et al. Image edge detection based on nonsubsampled contourlet transform and mathematical morphology[J].Journal of Southeast University(English Edition), 2012, 28(4):445-450.[doi:10.3969/j.issn.1003-7985.2012.04.013]
Last Update: 2012-12-20