Image Segmentation Based on Wavelet Transform

Abstract:

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Image segmentation is one of the fundamental problems in image processing and computer vision. Studies of high quality image segmentation methods have always gained a lot of attention in the field of image processing. However,so far the problem of image segmentation has not been well solved yet. Conventional methods cannot divide the images exactly because too much objectivity has been used. For complex objects, this paper proposed an efficient image segmentation algorithm based wavelet transform. This article presents the result of wavelet image segmentation and watershed algorithm image segmentation. The experimental result indicates that, the algorithm based on wavelet transform has fast convergence and good noise immunity.

Info:

Periodical:

Advanced Materials Research (Volumes 225-226)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

1041-1044

DOI:

10.4028/www.scientific.net/AMR.225-226.1041

Citation:

X. Q. Wang et al., "Image Segmentation Based on Wavelet Transform", Advanced Materials Research, Vols. 225-226, pp. 1041-1044, 2011

Online since:

April 2011

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Price:

$35.00

[1] Hu Changhua, Zhang Junbo, Xia Junzhang, zhang fei. Based on MATLAB system analysis and design—Wavelet analysis [M]. Xi'an: Xidian University Publishing, (1999).

[2] B.T.M. Roerdink,, A. Meijster. The watershed transform: definitions,, algorithms and Parallelization [J]. Fundamental Informational,, 2000,, 41: 187-228.

[3] Lotufo R,, Silva W,, Minimal set of markers for the watershed transform [J]. Proceedings of ISMM 2002,, Redistribution rights reserved CSIRO Publishing,, 2002,, 359-368.

[4] Volker M,, Thiers C,, Lehaman T. Segmentation of medical images by feature tracing in a self dual Morphological scale-space [J]. Proceedings of SPIE,, 2002,, vol. 4322: 139-150.

[5] Li Chung Ming, Xu Cheng yang, Gui Chang feng. Level set evolution without re-initialization: A new variation formulation [A]. IEEE Proceedings of Computer Vision and Pattern Recognition (CVPR' 05) [C]. 2005. P667-670.

DOI: 10.1109/cvpr.2005.213

[6] Xiao Chang yan, Zhang Su, Chen Ya zhu. Fast image segmentation based on a two-stage geometrical active contour[J]. Journal of Shanghai University, 2005, 9(1): 40-45.

DOI: 10.1007/s11741-005-0102-2

[7] Wang ai Ming. Image segmentation research review [J]. Microcomputer Applications, 2000, 27(5), P1-5.

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