Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

Wei Wei

doi:10.4028/www.scientific.net/AMM.631-632.470

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 631-632Wave Equalization - A New Image Enhancement Method...

Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

Abstract:

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

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Periodical:

Applied Mechanics and Materials (Volumes 631-632)

Pages:

470-473

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.631-632.470

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Online since:

September 2014

Authors:

Wei Wei*

Keywords:

Image Binarization, Image Segmentation, Non-Destructive Test Image, Uneven Illumination

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* - Corresponding Author

References

[1] N. Otsu. A thresholding selection method from gray-scale histogram. IEEE Transactions on System, Man, and Cybernetics, Vol. 9 (1979), p.62 – 66.

Google Scholar

[2] I. T. Jolliffe. Principal Component Analysis. New York: Springer-Verlag, (2002).

Google Scholar

[3] L Ma, R C Staunton. A modified fuzzy C-means image segmentation algorithm for use with uneven illumination patterns. Pattern Recognition, Vol. 40 (2007), pp.3005-3011.

DOI: 10.1016/j.patcog.2007.02.005

Google Scholar

[4] I. K. Kim, D. W. Jung, R. H. Park. Document image binarization based on topographic analysis using a water flow model. Pattern Recognition, Vol. 35(2002), p.265 – 277.

DOI: 10.1016/s0031-3203(01)00027-9

Google Scholar

[5] M. Sezgin, B. Sankur. Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging, Vol. 13 (2004), p.146 – 168.

DOI: 10.1117/1.1631315

Google Scholar