一种建筑物目标识别方法  

Approach to Building Recognition

作　　者：金泰松[1] 李翠华[2] 魏本杰[1] 

机构地区：[1]北京理工大学计算机科学技术学院计算机科学工程系,北京100081 [2]厦门大学信息科学与技术学院,福建厦门361005

出　　处：《计算机工程与应用》2006年第33期1-3,共3页Computer Engineering and Applications

基　　金：国家创新研究群体资助项目(60024301);国家自然科学基金资助项目(60175008);厦门大学985二期信息创新平台项目资助

摘　　要：论文提出了一种在复杂场景图像中识别建筑物目标的方法。提取图像的短线段特征,将目标识别转化为最大后验概率估计问题,并利用贝叶斯理论将先验知识引入到识别过程中。利用概率分布表示模板特征在匹配过程的不确定性,反映了目标在被遮挡条件下,不匹配的模板特征分布聚集的现象。利用高斯分布表示图像特征的不确定性。最终给出一个评判分数判断图像中存在建筑物目标的区域。实验表明:给出的评判分数能在一定程度上排除图像中虚假目标,识别出真正目标。This paper presents a new approach to recognize object of building in complex scenes. It extracts a set of llne segments,and turns object recognition into maximum a posteriori estimation.The prior knowledge can be incorporated into target identification process by using Bayesian theory.A distribution is proposed to model the uncertainty of model features,which captures phenomena such as the fact that the unmatched features due to partial occlusion are generally spatially correlated rather than independent.Fluctuations of matched image features are modeled by Gauss distribution.Finally,a score is proposed to evaluate the region of image,where buildings may exist.Experiments on the natural image sets demonstrated that the proposed score to a certain extent can differentiate between the true object and the false object in complex scenes.

关 键 词：贝叶斯 吉布斯分布 高斯分布 短线段 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]