A Morphological Gradient Approach to Color Edge Detection

Adrian N Evans; X U Lin

doi:10.1109/TIP.2005.864164

A Morphological Gradient Approach to Color Edge Detection

Adrian N Evans, X U Lin

Department of Electronic & Electrical Engineering

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176 Citations (SciVal)

267 Downloads (Pure)

Abstract

A morphological gradient approach to color edge detection Evans, A.N.; Liu, X.U.; Image Processing, IEEE Transactions on Volume 15, Issue 6, June 2006 Page(s):1454 - 1463 Abstract: A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.

Original language	English
Pages (from-to)	1454-1463
Number of pages	10
Journal	IEEE Transactions on Image Processing
Volume	15
Issue number	6
DOIs	https://doi.org/10.1109/TIP.2005.864164
Publication status	Published - Jun 2006

Keywords

Color image processing
edge detection
morphological operations

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10.1109/TIP.2005.864164

IEEETIPJune2006.pdf
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AB - A morphological gradient approach to color edge detection Evans, A.N.; Liu, X.U.; Image Processing, IEEE Transactions on Volume 15, Issue 6, June 2006 Page(s):1454 - 1463 Abstract: A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.

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A Morphological Gradient Approach to Color Edge Detection

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