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

机译:一种基于多层次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:由于复杂和照明不对称,一些图像很难通过常规方法进行有效分割。本文设计并提出了一种基于多级特征的算法,该算法可用于从噪声,干扰,照度不均匀,场景多变的图像中提取目标。该算法首先将原始图像转换为灰色图像。然后从高层或低层特征消息中继承地提取目标的每个层的特征。此外,它还可以追溯到原始图像或低级特征,并通过递归进行提取。因此目标可以与背景分离。算法实验结果表明,该算法能够高效,高精度地提取目标,并且具有不同的目标大小和信噪比。

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