Watershed Segmentation Based on Morphological Scale-Space and Gradient Modification

Wang Xiao-peng; Hao Chong-yang; Fan Yang-yu

Volume 28 Issue 3

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Article Navigation > Journal of Electronics & Information Technology > 2006 > 28(3): 485-489

Wang Xiao-peng, Hao Chong-yang, Fan Yang-yu. Watershed Segmentation Based on Morphological Scale-Space and Gradient Modification[J]. Journal of Electronics & Information Technology, 2006, 28(3): 485-489.

Citation:

Wang Xiao-peng, Hao Chong-yang, Fan Yang-yu. Watershed Segmentation Based on Morphological Scale-Space and Gradient Modification[J]. Journal of Electronics & Information Technology, 2006, 28(3): 485-489.

Citation:

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Watershed Segmentation Based on Morphological Scale-Space and Gradient Modification

Received Date: 2004-08-23
Rev Recd Date: 2004-12-28
Publish Date: 2006-03-19

Abstract

Abstract

A method for watershed image segmentation based on morphological scale-space and gradient modification is proposed to avoid over-segmentation and the drawbacks of some improved watershed segmentations. Firstly, morphological hybrid opening and closing by reconstruction scale-space is employed to smooth the original image, after smoothing, the essential region contours are preserved and unimportant details and noise which are often the causes of over-segmentation are removed, and the problem of the traditional morphological opening and closing scale-space, including the lost of partial essential region contours and not satisfying scale causality, are both avoided. Secondly, in order to eliminate over-segmentation and to keep the scale causality from the extreme to the segmented regions, gradient modification is used before the standard watershed transform, to remove the regional minimum in the gradient image caused by the regional maximum in the smoothed image. Simulations show that this method can efficiently not only avoid over-segmentation, but also satisfy scale causality, and the localization of region contours is precise.

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References

赵建伟，王朋，刘重庆. 基于小波变换的分水岭图像分割方法,光子学报, 2003, 32(5): 602604. .[2]Wang D. A multiscale gradient algorithm for image segmentation using watersheds[J].Pattern Recognition.1997, 30(12):2043-[3]Jackway P T. Gradient watershed in morphological scale-space[J].IEEE Trans. on Image Processing.1996, 5(6):913-[4]胡巍, 张桂林, 陈朝阳. 一种基于尺度空间理论的高斯平滑方法. 数据采集与处理, 1998, 13(3): 276279. .[5]Heijmans H J A M, Van D B R. Algebraic framework for linear and morphological scale-spaces[J].Journal of Visual Communication and Image Representation.2002, 13(3):269-[6]Jackway P T, Deriche M. Scale-space properties of the multiscale morphological dialation-erosion. IEEE Trans. on Pattern Anal. Machine Intell., 1996, 18(1): 3851. .[7]Volker M, Christian T, Thomas L. Segmentation of medical images by feature tracing in a selfdual morphological scale-space. Proceedings of SPIE, 2001, 4322: 139150. .[8]Lee C K, Wang S P. A mathematical morphological approach for segmenting heavily noise corrupted images[J].Pattern Recognition.1996, 29(8):1347-[9]Beucher S. Geodesic reconstruction, saddle zones hierarchical segmentation. Image Anal. Stereol., 2001, 20(2): 137.141.[10]Vicent L. Morphological grayscale reconstruction image analysis: Application and efficient algorithms[J].IEEE Trans. on Image Processing.1993, 2(4):176-[11]Salembier P. Morphological multiscale segmentation for image coding. Signal Processing, 1994, 38(3): 359386.

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