Zernike moment and local distribution fitting fuzzy energy-based active contours for image segmentation

NCUIR > College of Electrical Engineering & Computer Science > Department of Electrical Engineering > journal & Dissertation > Item 987654321/108565

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/108565

Title:	Zernike moment and local distribution fitting fuzzy energy-based active contours for image segmentation
Authors:	徐國鎧;Tran, Thi-Thao;Pham, Van-Truong;Shyu, Kuo-Kai
Contributors:	資訊電機學院電機工程學系
Keywords:	Computer Imaging;Computer Science;Image Processing and Computer Vision;Multimedia Information Systems;Original Paper;Pattern Recognition and Graphics;Signal,Image and Speech Processing;Vision
Date:	2014-01-01
Issue Date:	2026-04-23 14:55:13 (UTC+8)
Publisher:	Springer London;London: Springer London
Abstract:	摘要： This paper presents a new region-based active contour model for extracting the object boundaries in an image, based on techniques of curve evolution. The proposed model introduces an energy functional that involves intensity distributions in local image regions and fuzzy membership functions. The local image intensity distribution information used to guide the motion of the contour, in the paper, is derived by Hueckel operator in the neighborhood of each image point. The parameters of Hueckel operator are estimated by a set of orthogonal Zernike moments before curve evolution. Meanwhile, the fuzzy membership functions are used to measure the association degree of each image pixel to the region outside and inside the contour. To minimize the energy functional, instead of solving the Euler–Lagrange equation of the underlying problem, the paper employs a direct method to compute the energy alterations. As a result, the model can deal with images with intensity inhomogeneity. In addition, the model effectively alleviates the sensitivity to contour initialization. Moreover, the model reduces computational cost, avoids problems associated with choosing time steps as well as allows fast convergence to the segmentation solutions. Experimental results on synthetic, real images and comparisons with other models show the desired performances of the proposed model. 其他題名： SIViP 出版者： London: Springer London 出版日期： 2014-01 出處： Signal, image and video processing, 2014-01, Vol.8 (1), p.11-25 版權： Springer-Verlag London 2012 識別號： ISSN: 1863-1703 識別號： EISSN: 1863-1711 識別號： DOI: 10.1007/s11760-012-0415-0
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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