蚁群alpha抠图:一种自然图像抠图的新方法

V. Soleimani, F. H. Vincheh
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引用次数: 0

摘要

本文提出了一种基于蚁群优化的自然图像前景和背景区域分离的交互式算法(自然图像抠图)。图像抠图是当今图像处理中最具挑战性和最有趣的研究领域之一。在我们的方法中,用户通过一些红色和蓝色的涂鸦来指定前景和背景区域,而不是准备一个trimap。然后通过最小化所有像素的局部能量函数来估计alpha哑光。我们的方法不仅需要与用户进行少量的交互,而且通过对彩色图像应用蚁群算法,找到图像的均匀区域,与其他方法相比,取得了良好的效果。换句话说,像素蚂蚁使用行进路径获得像素的局部能量,并且由于蚂蚁倾向于移动到与起始像素相似的像素,因此检测到图像的均匀区域。此外,我们在算法的实现中使用了一些技术,如向量化,以降低时间复杂度。实验结果表明了算法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ant colony alpha matte: A new approach for natural image matting
In this paper, we present an interactive algorithm to separate foreground and background regions of natural images (natural image matting) using ant colony optimization. Today, image matting is one of the most challenging and interesting research fields in image processing. In our approach instead of preparing a trimap, the user specifies foreground and background regions by some red and blue scribbles. Then by minimizing local energy function of all pixels alpha matte is estimated. Our approach not only needs a little interaction with the user but also by applying ant colony algorithm on color images, finds homogenous regions of the image and yields good results compared with other methods. In other words, the local energy of a pixel is obtained using traveled path by the pixel ant and since the ant tends to move to pixels similar to beginning pixel, homogenous regions of the image are detected. Moreover, we use some techniques like vectorization in the implementation of our algorithm in order to decrease time complexity. Experimental results show our algorithm advantages.
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