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

H. Dong, P. Zhao, X. Wang
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Abstract

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.
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一种基于多层次特征的递归目标提取方法
由于图像分割的复杂性和光照的不对称性,一些常规的图像分割方法难以有效分割。本文设计并提出了一种基于多层次特征的目标提取算法,该算法可用于噪声较多、干扰较大、光照不均匀、场景多变的图像中目标的提取。该算法首先将原始图像转换为灰度图像。然后从高阶或低阶特征信息中继承提取目标的每一阶特征。此外,该方法还可以跟踪到原始图像或低层次特征,并通过递归的方式进行提取。这样目标就能从背景中分离出来。实验结果表明,该算法能够正确提取目标,提取效率高,提取精度高,而且目标大小和信噪比也不同。
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