为了准确分离图像中的对象与背景信息，并使得分离效果不受图像中光照变化的影响，提出了一种改进的图像背景减除算法。首先，算法使用改进的图割方法进行背景减除，提高减除效果。其次，算法提出颜色衰减模型和对比度衰减模型，改进能量公式中的颜色分量和对比度分量，消除光照变化对于减除结果的影响。最后，针对分离出的二值图像，提出利用形态学操作和空洞填充策略予以优化补偿，优化最终图像分离的结果。实验结果表明，当原始图像和背景图像光线强度差别较大，或光线被对象遮挡的情况下，相比于传统背景减除算法，该算法的减除效果仍然较好。该算法适用于复杂环境下图像中对象提取。

In order to extract object from images correctly and to ensure good results under illumination changing between images, a new background cut algorithm is proposed. First, an improved graph cut method is used to enhance the cutting results. Then the color and contrast attenuation models are presented to replace the color term and the contrast term in energy function which will reduce the infection due to illumination. Finally, we use morphology operation and holes filling methods to increase the final effect. Experimental results indicate that this algorithm is more effective than traditional background cut algorithms especially when the source image and the background image hold different illuminations or when light is covered by the object. It can satisfy the system requirements of extracting object in complex environments.