面向逆反射体检测的特征显著性研究

项目名称： 面向逆反射体检测的特征显著性研究

项目编号： No.61503394

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 杨星

作者单位： 中国人民解放军国防科技大学

项目金额： 20万元

中文摘要： 回归反射体被广泛应用于车牌、道路标识、以及其他辅助标识。在不可控交通环境中实现这些标识的自动检测是智能交通系统中人、车、路综合状态分析的核心支撑技术。越显著的特征对成功检测的贡献越大，显著性特征融合是提高检测鲁棒性的重要手段，而逆反射特性是交通标识更具有本原性和可分性的特征。因此，本课题拟重点研究面向目标检测的逆反射特性量化与特征显著性建模。通过主动成像机制将目标的逆反射特性量化为易于提取和分析的亮度信息。利用概率统计为度量标准，分别计算逆反射特性、颜色、形状三种特征导致错误分类的最小概率，作为特征显著性的定量描述。依据显著性设计多特征融合检测算法。最后，分析和评价量化模型、显著性计算模型、以及检测算法的性能，总结出适合复杂条件下逆反射体检测的方法。研究成果有望为其他光学合作目标的检测与识别提供一定的借鉴。

中文关键词： 特征选择；特征显著性；逆反射；交通标识

英文摘要： Retroreflection object is widely used in license plate, road sign, and other auxiliary sign. Realizing automatic detection of these signs in uncontrollable traffic condition is the core technology for comprehensive state analysis of men, vehicle, and road in Intelligent Traffic Systems. Since the more salient a feature is, the greater contribution it makes to successful detection, salient feature fusion plays an important role in enhancing detection robustness. And retroreflection characteristic of traffic sign is much more salient and discriminable. Hence, we focus on the retroreflection characteristic quantification and feature salience modelings orienting towards object detection in this research. By an active imaging machnism, retroreflection characteristic is quantified as luminance information that is easier to be extracted and analyzed. The minimum probabilities of false calssification caused by retroreflection characteristic, color, and shape are calculated as quantitative descriptions of feature salience, respectively, relying on probability statistics criterion. And a detection algorithm based on multi feature fusion is devised according to this salience. Finally, performances of the quantifization model, the salience computation model, and the detection algorithm are analyzed and estimated, so as to providing a method of retroreflection object detection, suitable for complex conditions. These achievements may profit detection and recognition of some other optical-cooperative objects.

英文关键词： feature selection;feature salience;retroreflection;traffic sign