退化图像不变性识别研究

项目名称： 退化图像不变性识别研究

项目编号： No.61201383

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 肖斌

作者单位： 重庆邮电大学

项目金额： 24万元

中文摘要： 图像的退化不变性识别通常是指图像几何畸变不变性识别，是提高计算机视觉系统自适应性的重要技术，但通常图像在发生几何畸变的同时也伴随灰度变换的退化（噪声、光照变化、对焦模糊、运动模糊等），单纯的图像几何畸变不变性识别往往不能满足图像退化识别的要求。本项目主要研究图像组合退化不变性识别问题，利用矩分析、图像变换和图像局部矩等方法从全局特征和局部特征两个角度去构造组合退化不变特征，然后进行图像分类或配准。另外，本项目还深入研究图像投影变换不变性识别和恶劣气候（大雾、沙尘）条件下引起的图像退化不变性识别问题，提出利用交叉矩和面积矩分析方法构造图像投影变换不变特征的新思路。为验证项目中所提出的算法的性能，以恶劣气候环境下的车牌和交通标志退化图像为例，建立图像退化模型和各种退化图像数据库并进行识别测试。本项目的成功实施，将对图像识别系统在工程实践特别是在图像质量受到影响的工程应用中起到一定的推动作用。

中文关键词： 退化图像；图像识别；特征提取；矩与不变矩；图像变换

英文摘要： Invariant image recognition is usually regarded as image recognition under geometric transform deformation such as translation, scale and rotation, it is an important technology to enhance the adaptivity of computer vision system and has been widely used in the field of pattern recognition and other similar applications. Since images which we acquired usually have been degraded by other deformation such as noise, illumination, defocus blur, motion blur, etc., image invariant recognition only under geometric transform deformation can not satisfy the demand of image recognition system. In this project, we mainly study the image invariant recognition problem under combined deformations by image moments analysis method, image transform and image local moments methods form both global invariant feature extraction and local invariant feature extraction points. In addition, we discuss the problem of projective invariant image recognition, invariant image recognition under fog (haze) deformation and the degradation modeling problem under sand storm deformation. We propse a new idea to contrstruct projective invariant features using Cross ratio moments and Area moments. In order to verify the performance of these algorithms proposed in this project, we use vehicle license plate and traffic sign images under adverse weat

英文关键词： Degraded image；Image recognition；Feature extraction；Moments and moment invariants；Image transforms