计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 1050-1052.DOI: 10.3724/SP.J.1087.2012.01050

• 人工智能 • 上一篇    下一篇

基于冲突再分配DSmT的多尺度融合边缘检测算法

乔奎贤1,尹诗白1,曲圣杰2   

  1. 1. 西安工业大学 计算机科学与工程学院, 西安 710032
    2. 西北工业大学 自动化学院,西安 710072
  • 收稿日期:2011-09-19 修回日期:2011-11-21 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 曲圣杰
  • 作者简介:乔奎贤(1970-),男,陕西宝鸡人,讲师,硕士,主要研究方向:图像处理、人工智能;
    尹诗白(1984-),女,四川成都人,博士研究生,主要研究方向:机器视觉、医学图像分割;
    曲圣杰(1982-),男,山东烟台人,博士研究生,主要研究方向:图像处理、证据推理。

Multi-scale fused edge detection algorithm based on conflict redistribution DSmT

QIAO Kui-xian1,YIN Shi-bai1,QU Sheng-jie2   

  1. 1. School of Computer Science and Engineering, Xian Technological University, Xi’an Shaanxi 710032, China
    2. School of Automation, Northwestern Polytechnical University, Xi’an Shaanxi 710072,China
  • Received:2011-09-19 Revised:2011-11-21 Online:2012-04-20 Published:2012-04-01
  • Contact: QU Sheng-jie

摘要: 由于实际景象地物特征复杂,单一尺度边缘检测算子提取的边缘与噪声点测度差异小,因此将导致细小地物与噪声相互掺杂,边缘提取不准确的现象。针对此问题,提出了一种基于冲突再分配DSmT的多尺度融合边缘检测算法。首先提取图像多尺度边缘测度,接着提出双向指数映射基本置信指派构造方法构造多尺度边缘测度基本置信指派,然后采用冲突再分配DSmT组合规则对多尺度边缘置信指派进行融合,最后根据融合后的边缘置信指派图通过双阈值法确定边缘像素。通过对可见光和合成孔径雷达(SAR)图像的仿真实验表明,该算法相比单一尺度的Canny算子在边缘提取过程减小了误检和漏检边缘点数目,在抑制噪声的同时,大量保留了景象细节信息。

关键词: 边缘检测, 冲突再分配, 多尺度边缘测度, 基本置信指派, 证据理论

Abstract: Single-scale edge detection operator itself is sensitive to noise, which leads to little difference between the real and false edge, so the edge detected by it is not accurate, because ground object character is complex and thin ground object is intermingled with noise in real environment. Therefore, a new multi-scale fused edge detection algorithm based on conflict redistribution DSmT was proposed in this paper. First, multi-scale edge measure was extracted and then evidence theory was brought in. The basic belief assignment of multi-scale edge measure was constructed by a new method of bidirectional exponent and then fused by conflict redistribution DSmT combination rule. At last, edge points were extracted by multiple thresholds. The simulation with both optical and Synthetic Aperture Radar (SAR) images shows that the edge detection method of this paper suppresses noise effectively, while preserving rich details.

Key words: edge detection, Conflict Redistribution (CR), multi-scale edge measure, Basic Belief Assignment (BBA), evidence theory