CAJ | 학술논문

针对现有的基于判别型或聚类型的图像,用分割方法无法处理被噪声污染的图像的现状,提出一种新的两步式图像分割框架.该框架首先利用图像的局部信息重塑图像的灰度直方图,增强了像素的类间散布性和类内紧凑性,然后将现有的基于判别型或基于聚类型图像分割方法在重塑图像上执行,从而提高了现有图像分割算法的有效性和鲁棒性.文中用典型的聚类型方法高斯混合模型来说明该框架的可行性.由于框架的两个步骤具有独立性,因此可推广到现有的其他基于像素或直方图的方法.在人工和真实图像上的实验结果证明,这种两步图像分割框架可以获得有效且鲁棒的图像分割结果.
침대현유적기우판별형혹취류형적도상,용분할방법무법처리피조성오염적도상적현상,제출일충신적량보식도상분할광가.해광가수선이용도상적국부신식중소도상적회도직방도,증강료상소적류간산포성화류내긴주성,연후장현유적기우판별형혹기우취류형도상분할방법재중소도상상집행,종이제고료현유도상분할산법적유효성화로봉성.문중용전형적취류형방법고사혼합모형래설명해광가적가행성.유우광가적량개보취구유독립성,인차가추엄도현유적기타기우상소혹직방도적방법.재인공화진실도상상적실험결과증명,저충량보도상분할광가가이획득유효차로봉적도상분할결과.
A new two-step framework is proposed for image segmentation. In the first step, the gray-value distribution of the given image is reshaped to have larger inter-class variance and less intra-class variance. In the second step, the discriminant-based methods or clustering-based methods are performed on the reformed distribution. It is focused on the typical clustering methods-Gaussian mixture model(GMM) and its variant to demonstrate the feasibility of the framework. Due to the independence of the first step in its second step, it can be integrated into the pixel-based and the histogram-based methods to improve their segmentation quality. The experiments on artificial and real images show that the framework can achieve effective and robust segmentation results.