The technology of automatic choose of threshold value is used, and it make the choose more reasonable . the graying arithmetic is improved in order to pick up interest point and target easily 本文在应用部分采用了自动阈值选择技术，使阈值的选择更合理；对灰度化算法进行了改进，目的是较容易的提取兴趣点和目标。
The variance normalized correlation is used to match the interesting points roughly in the first phase . the rough match is accurate in some extent because unicity and symmetry are imposed on the correlation 第一个阶段使用规一化相关来进行特征点的粗略匹配,由于在规一化相关上加入了单一性和对称性的限制,粗略匹配有着较好的精度。
This is a feature-based method which using harris interesting points of images . based on the user ’ s input images, the method will find the arrangement information and output panorama automatically 该算法基于图像的harris特征点,用户只需要输入待拼接图像集合,自动图像拼接算法将完成图像序列位置关系的寻找、图像的拼接、全景图的生成。
Based on these three criteria, an improved interest points detection algorithm is presented after we theoretically analyze the characteristics around the interest points and compare different detectors according to the criteria specified above 根据这三个准则，在系统分析了兴趣点及其周围邻域的特性，并对已有的兴趣点检测算法进行研究比较后，本文给出了一种改进的兴趣点检测算法。
Based on these three criteria, an improved interest points detection algorithm is presented after we theoretically analyze the characteristics around the interest points and compare different detectors according to the criteria specified above 根据这三个准则，在系统分析了兴趣点及其周围邻域的特性，并对已有的兴趣点检测算法进行研究比较后，本文给出了一种改进的兴趣点检测算法。
Afterwards, the image is represented by the color feature of small areas centered at extracted interest points . this feature combines the shape feature implied by interest points with color feature extracted from those small areas, which decides the similarity between two images 接下来利用兴趣点周围区域的颜色特征来代表图象的特征，这样，兴趣点的形状特征就和其周围区域的颜色特征有机的结合起来，图象间相似度的计算就基于这种特征。
Afterwards, the image is represented by the color feature of small areas centered at extracted interest points . this feature combines the shape feature implied by interest points with color feature extracted from those small areas, which decides the similarity between two images 接下来利用兴趣点周围区域的颜色特征来代表图象的特征，这样，兴趣点的形状特征就和其周围区域的颜色特征有机的结合起来，图象间相似度的计算就基于这种特征。
The detection of interest points is the basis of kinds of computer vision applications, such as : camera calibration, 3d reconstruction, image matching, video retrieval, motion estimation, etc . in this paper, three impersonal criteria : delocalization, false-detection rate, and repeatability are presented to evaluate the performance of an interest points detection algorithm 兴趣点检测是许多计算机视觉应用的基础，如：摄像机定标、三维重建、图像匹配、视频检索、运动估计等。本文首先给出了一个评价兴趣点检测算法性能的客观标准，这个标准包括以下三个准则：点位置偏差、误检率及重复度。
