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Image Sequences Segmentation Algorithm Based on Wavelet Transformation with Timeline

机译:基于小波变换与时间轴的图像序列分割算法

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Presently, image sequences segmentation algorithm can be mainly separated into two parts. One is based on brightness, chroma and margin pixel information, the other is based on frame disparity information, just like Frame Disparity Threshold, Change Detection Mask (CDM), High Order Statistic (HOS) and so on. The first method is seldom used recently, while the latter one is deficient in noise-sensitive. So, we take a special point of view in this paper, and presented a new segmentation algorithm based on wavelet with timeline method. Here timeline is offered to control time sequences. Firstly, we transform the image sequences by wavelet on the timeline. After the transformation, we should hold the high-frequency coefficient on the part of motion, and then we obtain motion object's mask by morphological process. By such a series of operations, we can get the final motion object. Finally we devise some experiments to measure the method's processing efficiency and real-time properties. The results show that the method is simple and practical.
机译:目前,图像序列分割算法可以主要分为两部分。一个基于亮度,色度和边距像素信息,另一个基于帧视差信息,就像帧视差阈值一样,改变检测掩码(CDM),高阶统计(HOS)等。最近第一种方法很少使用,而后者的噪声敏感性很少。因此,我们在本文中进行了特殊的观点,并介绍了具有时间线方法的基于小波的新分割算法。这里提供时间线来控制时间序列。首先,我们在时间轴上通过小波转换图像序列。在转换之后,我们应该在运动部分上保持高频系数,然后通过形态过程获得运动对象的掩模。通过这样的一系列操作,我们可以获得最终的运动对象。最后,我们设计了一些实验来测量方法的处理效率和实时性质。结果表明,该方法简单实用。

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