CAJ | 학술논문

针对测地线活动轮廓（GAC）模型不能对包含噪声和灰度不均匀现象这类复杂背景图像成功提取目标的问题，本文提出局部熵驱动的GAC模型。首先提取图像的局部信息熵来刻画图像的灰度变化，再利用局部熵构造符号压力函数来指导轮廓曲线向目标边界靠近，实现目标的分割。为降低计算复杂度并提高模型对水平集变化的鲁棒性，采用二值水平集方法进行求解。实验结果表明，本文方法可以克服噪声和灰度不均匀对图像分割的影响，实现快速准确的分割。
침대측지선활동륜곽（GAC）모형불능대포함조성화회도불균균현상저류복잡배경도상성공제취목표적문제，본문제출국부적구동적GAC모형。수선제취도상적국부신식적래각화도상적회도변화，재이용국부적구조부호압력함수래지도륜곽곡선향목표변계고근，실현목표적분할。위강저계산복잡도병제고모형대수평집변화적로봉성，채용이치수평집방법진행구해。실험결과표명，본문방법가이극복조성화회도불균균대도상분할적영향，실현쾌속준학적분할。
The geodesic active contour model (GAC)can′t identify the object of the images with complex background such as noise and intensity inhomogeneities successfully .For this reason ,this paper proposes GAC model driven by the local entropy .First of all ,the local information entropy of image is abstracted to describe the local intensity variation .Then ,the signed pressure force func-tion based on the local entropy are structured ,which guides the contour curve close to the boundary of the object and achieves the segmentation of the object .In order to reduce the computational complexity and improve the robustness of the proposed model to different level sets ,the proposed method is implemented by the binary level set method .The experimental results show that this method can overcome the influence of complex background to the segmentation results ,and realize fast and accurate segmentation .