柔性矢量形态学梯度算子

雷涛; 樊养余; 王小鹏

doi:10.3969/j.issn.1001-0548.2014.06.020

柔性矢量形态学梯度算子

1.
兰州交通大学电子与信息工程学院兰州 730070;
2.
西北工业大学电子信息学院西安 710072

基金项目:

国家自然科学基金(61461025,61202314,61261029);中国博士后科学基金(2012M521801);中国博士后特别资助项目(2014T70937)

详细信息

作者简介:
雷涛(1972-),男,博士,主要从事图像处理、模式识别等方面的研究.

中图分类号: TP391.4
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出版历程
- 收稿日期: 2013-09-11
- 修回日期: 2014-01-29
- 刊出日期: 2014-12-14

Soft Vector Morphological Gradient Operators

1.
School of Electronics and Information Engineering,Lanzhou Jiaotong University Lanzhou 730070;
2.
School of Electronics and Information,Northwestern Polytechnical University Xi'an 710072

摘要

摘要: 经典的形态学梯度算子不能直接拓展到彩色图像处理中,现有的矢量形态学梯度算子对噪声较为敏感且性能较低。为解决该问题,提出了一种新的柔性矢量形态学梯度算子,并将其应用到彩色图像边缘检测中。新的形态学梯度算子利用柔性形态学原理有效地降低了噪声对彩色图像边缘的影响,从而提高了矢量形态学梯度算子的抗干扰能力。实验结果表明,新的柔性矢量形态学梯度算子在噪声条件下能获得较好的矢量梯度,对彩色图像的后续分割及目标识别具有重要的作用。
- 彩色图像处理 /
- 边缘检测 /
- 柔性形态学算子 /
- 矢量排序
Abstract: Since classical morphological gradient operator cannot be directly extended to color image processing, the existing vector morphological gradient operator is sensitive to noise and it has low performance. This paper proposes a new soft vector morphological gradient operator and applies it in the edge detection of color images in order to solve the problem. New morphological gradient operator takes the advantage of soft morphology theory, which effectively reduces the influence of noise on the edge, so as to improve the anti-interference ability of the vector morphological gradient operator. Experimental results show that compared with the existing vector morphological gradient operators, the new soft vector morphology gradient operators achieve better gradient vector in the case of noise, and plays an important role in the following steps of color image segmentation and recognition.
- color image processing /
- edge detection /
- soft morphological operators /
- vector ordering