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首页> 外文会议>International Carnahan Conference on Security Technology >A novel background subtraction method based on color invariants and grayscale levels
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A novel background subtraction method based on color invariants and grayscale levels

机译：基于颜色不变性和灰度级的背景减除新方法

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This paper presents a new method for background subtraction which takes advantages of using the color invariants combined with gray color. The proposed method works robustly reducing misclassified foreground objects. Gaussian mixtures are exploited for each pixel through two channels: the color invariants, which are derived from a physical model, and the gray colors obtained as a descriptor of the image. The background models update is performed using a random process selected considering that in many practical situations it is not necessary to update each background pixel model for each new frame. The novel algorithm has been compared to three state-of-the-art methods. Experimental results demonstrate the proposed method achieves a higher robustness, is less sensitive to noise and increases the number of pixel correctly classified as foreground for both indoor and outdoor video sequences.
机译：本文提出了一种新的背景扣除方法，该方法利用了将不变量与灰色相结合的优势。所提出的方法有效地减少了误分类的前景对象。高斯混合通过两个通道用于每个像素：从物理模型派生的颜色不变性，以及作为图像描述符获得的灰色。考虑到在许多实际情况下不必为每个新帧更新每个背景像素模型，使用选择的随机过程执行背景模型更新。该新颖算法已与三种最新方法进行了比较。实验结果表明，该方法具有较高的鲁棒性，对噪声不敏感，并且增加了室内和室外视频序列正确分类为前景的像素数量。

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