The new MPEG-4 video coding standard enables content-based functions. In order to support the new standard, frames should be decomposed into Video Object Planes (VOP), each VOP representing a moving object. This paper proposes an image segmentation method to separate moving objects from image sequences. The proposed method utilizes the spatial-temporal information. Spatial segmentation is applied to divide each image into connected areas and to find precise object boundaries of moving objects. To locate moving objects in image sequences, two consecutive image frames in the temporal direction are examined and a hypothesis testing is performed with Neyman-Pearson criterion. Spatial segmentation produces a spatial segmentation mask, and temporal segmentation yields a change detection mask that indicates moving objects and the background. Then spatial-temporal merging can be used to get the final results. This method has been tested on several images. Experimental results show that this segmentation method is efficient.

滤波技术是指纹预处理中的关键步骤。本文提出了一种基于脊向指纹滤波预处理方法。首先利用改进后的极值滤波器对指纹图像进行滤波，再用本文所提出的脊向滤波器对结果进行处理，实验结果验证了此方法的有效性。

指纹识别技术因其在身份识别方面的重要性及具有广阔的应用前景而得到了广泛的研究。但目前的指纹识别算法存在特征提取精度不高。运算时间长等缺点，这里提出一种新的基于指纹脊线采样的指纹识别算法，克服了以往算法的缺点，取得了良好的实验效果。

本文在概要介绍小波变换的基础上，给出了小汉变换的边缘检测理论。导出了采用紧支集3次样条小波作为边缘检测的方法。最后给出了实验例子，验证了方法的有效性。