计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2014年
2期
198-200,204
,共4页
图像分割%活动轮廓模型%FCM聚类%RSF模型
圖像分割%活動輪廓模型%FCM聚類%RSF模型
도상분할%활동륜곽모형%FCM취류%RSF모형
Image segmentation%Active contour model%FCM clustring RSF model
针对现有活动轮廓模型初始化敏感的缺点,提出一种新的基于区域的活动轮廓模型。该模型采用模糊c 均值聚类(FCM)算法对图像进行预分割,将预分割结果二值化为种子标记矩阵,作为下一步水平集演化的初始轮廓,解决了初始化敏感问题;引用RSF(Region-Scalable Fitting)模型的局部区域项作为能量项,提高了分割灰度分布不均匀图像能力;使用高斯滤波方法正则化水平集函数,避免了重新初始化过程,提高了分割效率。实验结果表明:该模型避免了初始化,具有分割结果精确、分割效率高的特点。
針對現有活動輪廓模型初始化敏感的缺點,提齣一種新的基于區域的活動輪廓模型。該模型採用模糊c 均值聚類(FCM)算法對圖像進行預分割,將預分割結果二值化為種子標記矩陣,作為下一步水平集縯化的初始輪廓,解決瞭初始化敏感問題;引用RSF(Region-Scalable Fitting)模型的跼部區域項作為能量項,提高瞭分割灰度分佈不均勻圖像能力;使用高斯濾波方法正則化水平集函數,避免瞭重新初始化過程,提高瞭分割效率。實驗結果錶明:該模型避免瞭初始化,具有分割結果精確、分割效率高的特點。
침대현유활동륜곽모형초시화민감적결점,제출일충신적기우구역적활동륜곽모형。해모형채용모호c 균치취류(FCM)산법대도상진행예분할,장예분할결과이치화위충자표기구진,작위하일보수평집연화적초시륜곽,해결료초시화민감문제;인용RSF(Region-Scalable Fitting)모형적국부구역항작위능량항,제고료분할회도분포불균균도상능력;사용고사려파방법정칙화수평집함수,피면료중신초시화과정,제고료분할효솔。실험결과표명:해모형피면료초시화,구유분할결과정학、분할효솔고적특점。
Aiming at the defect of existing active contour model that it is sensitive to initialisation,we propose a new region-based active contour model in this paper.This model uses the fuzzy C-means clustering (FCM)algorithm to pre-segment the image,and binarise the results of pre-segmentation to the seed tagged matrix,which solves the problem of initialisation sensitivity;The local area item of the RSF(region-scalable fitting)model is adopted as the energy item,which improves the ability of segmenting the images with inhomogeneous grey distribution;In numerical calculation,Gaussian filtering is utilised to regularise the level set function,which prevents the process of re-initialisation and improves segmentation efficiency.Experimental results show that the proposed model prevents the re-initialisation,it has the characteristics of accurate in segmentation result and high in segmentation efficiency.