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Fusion of intensity and inter-component chromatic difference for effective and robust colour edge detection

机译:融合强度和组件间色差,实现有效而稳健的色彩边缘检测

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摘要

Edge detection, especially from colour images, plays very important roles in many applications for image analysis, segmentation and recognition. Most existing methods extract colour edges via fusing edges detected from each colour components or detecting from the intensity image where inter-component information is ignored. In this study, an improved method on colour edge detection is proposed in which the significant advantage is the use of inter-component difference information for effective colour edge detection. For any given colour image C, a grey D-image is defined as the accumulative differences between each of its two colour components, and another grey R-image is then obtained by weighting of D-image and the grey intensity image G. The final edges are determined through fusion of edges extracted from R-image and G-image. Quantitative evaluations under various levels of Gaussian noise are achieved for further comparisons. Comprehensive results from different test images have proved that this approach outperforms edges detected from traditional colour spaces like RGB, YC,bCr and HSV in terms of effectiveness and robustness.
机译:边缘检测,尤其是彩色图像的边缘检测,在图像分析,分割和识别的许多应用中起着非常重要的作用。大多数现有方法是通过融合从每个颜色分量检测到的边缘或从强度图像检测到的,其中分量间信息被忽略,从而提取颜色边缘。在这项研究中,提出了一种改进的彩色边缘检测方法,其中的显着优势是利用分量间差异信息进行有效的彩色边缘检测。对于任何给定的彩色图像C,将灰色D图像定义为其两个颜色分量之间的累积差,然后通过对D图像和灰度强度图像G进行加权获得另一个灰度R图像。通过融合从R图像和G图像提取的边缘来确定边缘。在各种高斯噪声水平下进行了定量评估,以作进一步比较。来自不同测试图像的综合结果证明,该方法在有效性和鲁棒性方面优于从传统颜色空间(如RGB,YC,bCr和HSV)检测到的边缘。

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  • 来源
    《Image Processing, IET》 |2010年第4期|p.294-301|共8页
  • 作者

  • 作者单位

    School of Informatics, University of Bradford, Bradford BD7 1DP, UK;

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  • 正文语种 eng
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