Abstract
A new LCV (local chan-vess) model algorithm based on prior shape focusing on segmentation of melon image is proposed in this paper to measure the micro changes of morphological parameters. During the process, local boundary information image of melon is acquired firstly through mathematical morphology algorithm, and construct LCV model according to the form of traditional CV model. After that, a prior shape can be obtained by mathematical morphology and spline interpolation algorithms, and then be integrated into LCV model functional through a shape comparing function, thus the LCV model based on prior shape is constructed. Compared with traditional edge detection and segmentation algorithms, the new algorithm proposed in this paper could obtain more ideal boundary information.
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References
Zhang, Y., Li, M., Liu, G., Qiao, J.: Separating Adjoined Apples Based on Machine Vision and Information Fusion. Transactions of the Chinese Society for Agricultural Machinery 40(11), 180–183 (2009)
Zeng, Q., Liu, C., Miao, Y., et al.: Non-destructive measurement of diameter of overlapping grape fruit based on morphological image processing. Transactions of the Chinese Society of Agricultural Engineering 25(9), 356–360 (2009)
Ying, Y., Gui, J., Rao, X.: Fruit shape classification based on Zernike moments. Journal of Jiangsu University (Natural Science Edition) 28(1), 1–3 (2007)
Mumford, D., Shah, J.: Optimal approximation by piecewise smooth functions and associated variational problems. Pure and Applied Mathematics 42, 577–685 (1989)
Chan, F.T., Vese, A.L.: Active contours without edges. IEEE Transactions on Image Processing 10(2), 266–277 (2001)
Min, H., Wang, X.: A New Fitting Model Based on Boundary Information. Electronics R&D 11, 7–10 (2010)
Paragios, N., Deriche, R.: Geodesic active regions: A new framework to deal with frame partition problems in computer vision. Int. J. Comput. Vis. 46(3), 223–247 (2002)
Darolti, C., Mertins, A., Bodensteriner, C., et al.: Local region descriptors for active contours evolution. IEEE Trans. Image Processing 17(12), 2275–2288 (2008)
Wang, X., Zhao, Y.: Liver CT image segmentation based on prior shape CV model. Journal of Optoelectronics Laser 21(6), 953–956 (2010)
Duan, X., Xia, D.: Level Set Model for Segmentation of Cardiac MRI Image Based on Ellipse Shape Restriction. Computer Engineering 33(16), 14–17 (2007)
Cremers, D., Sochen, N., Schrorr, C.: Towards recognition based variational segmentation using shape priors and dynamic labeling. In: Griffin, L.D., Lillholm, M. (eds.) Scale-Space 2003. LNCS, vol. 2695, pp. 388–400. Springer, Heidelberg (2003)
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Miao, Y., Zhu, Q. (2011). Melon Image Segmentation Based on Prior Shape LCV Model. In: Wang, Y., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25664-6_63
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DOI: https://doi.org/10.1007/978-3-642-25664-6_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25663-9
Online ISBN: 978-3-642-25664-6
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