基于IR的水平集进化阴影图像分割

R. Ganta, Syed Zaheeruddin, Narsimha Baddiri, R. Rameshwar Rao
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摘要

由于在不同的光照条件下进行图像采集,图像中嵌入了不均匀的强度区域。传统方法对此类图像的分割效果较差。本文通过在水平集演化过程中引入一种新的自适应力函数,提出了一种水平集方法。力函数由图像中的反射率和光照导出。该方法排除了图像中存在的阴影区域,成功地分割了图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IR based Level Set Evolution for segmentation of shadow images
Inhomogeneous intensity regions get embedded into the images due the result of image acquisition done under various lightening conditions. Segmentation of such images by using traditional methods shows poor results. In this paper we propose a Level set method by introducing a new adaptive force function on the level sets evolution. The force function is derived from reflectance & illuminations present in the image. This method is proved to be successful in segmentation of images by excluding the shadow regions present in the images.
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