图像前景提取算法的数值分析与比较

Guohua Wu, Jiangliang Li, Yong Jiang
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引用次数: 0

摘要

前景提取广泛应用于模式识别、电影、艺术等领域。前景提取中最重要的部分是图像边缘的检测。通过检测图像边缘,建立模型,通过区域、像素或颜色提取图像的前景。本文首先对几种典型的边缘检测算子算法进行了分析和评价,然后提出了一种基于前景和背景颜色基本模型的混合高斯模型来平衡这两种模型的不足。然后从混合高斯模型中得到矩阵E(x),然后通过最大流量最小切割算法实现前景提取。最后,随着参数的变化,分析了提取效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical Analysis and Comparison of the Algorithms of Image Foreground Extraction
Foreground extraction is widely used in pattern recognition, movie and arts, etc. And the most important part of Foreground extraction is detecting the image edge. By detecting the image edge, we can build the models to extract foreground from the image through region, pixel or color. This paper begin with the analysis and evaluation of several typical algorithms of edge detection operator, and then the mixture Gaussian model which based on the foreground and background colors basic model is given to balance the insufficient of two models. Next we get matrix E(x) from the mixture Gaussian model, and then realize foreground extraction by maximum flow minimum cut algorithm cutting. Finally as the parameter's change, the extracted effect is analyzed.
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