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A method of recursive target extraction based on multi-level features

机译:一种基于多级别特征的递归目标提取方法

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Due to the complexity and asymmetrical illumination, some images are difficult to be effectively segmented by some routine method. In this paper, an algorithm based on multi-level features is designed and proposed, and which can be used for target extraction from the images with more noises, interference, uneven illumination and changeable scene. The algorithm first transfers the original image into a gray one. And then features of every level the target are extracted inheritably from the high or low level feature message. Furthermore, it also can track back to the original image or the features of low level, and the extraction goes on by recursion. So the target can be separated from the background. The algorithm experiment results indicates the target can be correctly extracted with high-efficiency and great precision, and with different sizes of the target and SNR also.
机译:由于复杂性和不对称的照明,一些常规方法难以有效地分割一些图像。在本文中,设计和提出了一种基于多级别特征的算法,并且可以用于具有更多噪声,干扰,不均匀照明和可变场景的图像的目标提取。该算法首先将原始图像传送到灰色的图像。然后,目标的特征目标是从高电平或低级特征消息中固有提取。此外,它还可以跟踪原始图像或低电平的功能,并且提取通过递归进行。所以目标可以与背景分开。算法实验结果表明,目标可以用高效率和极高精度正确提取,以及不同尺寸的目标和SNR。

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