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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

Explore research outputs by the European Policies Research Centre...

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

Ren, Jinchang and Jiang, J. and Wang, D. and Ipson, S. (2010) Fusion of intensity and inter-component chromatic difference for effective and robust colour edge detection. IET Image Processing, 4 (4). pp. 294-301.

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Abstract

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, YCbCr and HSV in terms of effectiveness and robustness.