A Novel Edge Detection Algorithm of Color Image

De Rui Song; Dao Yan Xu; Li Li

doi:10.4028/www.scientific.net/AMM.446-447.976

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 446-447A Novel Edge Detection Algorithm of Color Image

A Novel Edge Detection Algorithm of Color Image

Abstract:

This paper proposes a novel algorithm of edge detection using LUV color space. Firstly, according to peer group filtering (PGF), a nonlinear algorithm for image smoothing and impulse noise removal in color image is used. Secondly, color image edges in an image are obtained automatically by combining an improved isotropic edge detector and a fast entropy threshold technique. Thirdly, according to color distance between the pixel and its eight neighbor-pixels, color image edges can further be detected. Finally, the experiment demonstrates the outcome of proposed algorithm in color image edge detection.

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Periodical:

Applied Mechanics and Materials (Volumes 446-447)

Pages:

976-980

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.446-447.976

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Online since:

November 2013

Authors:

De Rui Song, Dao Yan Xu, Li Li

Keywords:

Edge Detection, Fast Entropy, LUV Color Space, Peer Group Filtering

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References

[1] R. Gonzalq, R. Wood, Digital Image Processing, Addison - Wesley, (1992).

Google Scholar

[2] K. R. Casteman, Fundamentals of Digital Image Processing, PreuticeHall, Englewood Cliffs, N. J, (1996).

Google Scholar

[3] S. E. El-Khamy, I. Ghaleb, Fuzzy Edge Detection With Minimum Fuzzy Entropy Criterion, IEEE MELECON. 5 (2002) 498-503.

DOI: 10.1109/melecon.2002.1014643

Google Scholar

[4] F.F. William, F. Marie-Josee, Integrating Edge Detection and Dynamic Modeling in Quantitative Analyses of Ecological Boundaries, Bioscience, 53(8) (2003).

DOI: 10.1641/0006-3568(2003)053[0730:iedadm]2.0.co;2

Google Scholar

[5] F.A. Cheikh, R. Hamila, M. Gabbouj and J. Astola, Impulse noise removal in highly corrupted color images, Proc. of ICIP, 1(1996) 997-1000.

DOI: 10.1109/icip.1996.559669

Google Scholar

[6] C.D. Kenney, Y. Manjunath, B.S. Hewer, Peer group image enhancement, Image Processing, IEEE Transactions, 10 (2001) 326 -334.

DOI: 10.1109/83.902298

Google Scholar

[7] Y.N. Deng, K. Charles, S.M. Michael and B.S. Manjunath. Peer Group Filtering And Perceptual Color Image Quantition, IEEE 1999 21-24.

Google Scholar

[8] J.P. Fan, K.Y. David, A.K. Yau, W. G. Elmagarmid, automatic image segmentation by integrating color-edge extraction and seeded region growing, IEEE transactions on image processing, 10(2001) 1454-1466.

DOI: 10.1109/83.951532

Google Scholar

[9] C.G. Rafael, E. W Richard, Digital Image Processing Third Edition, Publishing House of electronics Industry, (2010).

Google Scholar