一种基于贝叶斯理论的目标验证方法
A New Approach to Object Verification Based on Bayesian Theory
-
摘要: 提出了一种验证图像中候选目标的新方案.综合目标的先验知识,将目标验证转化为给定候选目标的条件下,图像特征观察集合的条件概率问题.同时,提取图像的短线段特征,利用短线段特征的观察,给出了一种目标验证方法排除复杂场景图像中虚假建筑物目标.在自然图像集上进行的实验表明,所提出的方法能有效排除虚假目标,满足处理自然图像的要求.Abstract: A novel framework of object verification is proposed.Integrating by the prior knowledge of object,object verification is turned into a conditional probability of a set of observable cues available conditioned upon an object hypothesis.Then features of short line segments are extracted,and a new algorithm which verifies objects of building in complex scenes is presented using observation of line segments,.Tests on natural image sets showed that the proposed algorithm could effectively eliminate false objects,and satisfy the request of processing natural images on time performance.
下载: