CASIA OpenIR  > 毕业生  > 博士学位论文
图像特征点检测与匹配研究
Alternative TitleA Study of Image Feature Point Detection and Matching
王旭光
Subtype工学博士
Thesis Advisor吴福朝
2009-05-28
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword特征检测 特征匹配 特征向量场 相关性度量 Feature Detection Feature Matching Feature Vector Field Correlation Measure
Abstract图像特征检测与匹配是计算机视觉中的基本问题,它们在图像配准、三维重建、物体识别、运动跟踪和视频理解等领域都具有广泛应用。本文工作主要集中于特征点的检测与匹配,主要创新点如下: 1. 利用梯度外积运算引入图像的外积能量,外积能量能有效增强图像的角点和大曲率的边缘点。在此基础上,提出了一种新的特征点检测算子,称之为MEP检测算子。MEP检测算子能检测出角点、大曲率的边缘点和Blob点,同时还具有图像旋转和线性光照的不变性。 2. 利用梯度内积和外积运算,引入梯度相关性与特征向量场,并提出了两种新的特征点匹配方法:梯度相关性描述子(GCD)与特征向量场描述子(FVD)。这两种描述子都具有图像旋转和线性光照的不变性,实验表明它们对图像仿射、模糊、JPEG和非线性光照变化也有很好的适应性。 3. 受Harris检测算子的启发,提出两种新的图像特征:Harris相关和Harris特征向量,并给出两种新的描述子:Harris相关描述子(HCD)和Harris特征向量描述子(HFVD)。这两种描述子都具有图像旋转和线性光照的不变性。实验表明,它们对图像仿射、模糊、JPEG和非线性光照变化也表现出很好的性能。
Other AbstractImage feature detection and matching is a key problem in many applications of computer vision, such as image registration, 3D reconstruction, object detection and video understanding. In this dissertation, the main work is focused on feature point detection and matching, and the main contributions include: 1. The exterior product energy is introduced by using exterior product operations of image gradients, which can effectively enhance corners and edge points with large curvature in images. Then, a feature point detector is proposed, namely maximum exterior product (MEP) detector. The MEP detector can not only detect corners and edge points with large curvature but also can detect blobs in images. In addition, it is invariant to image rotation and linear change of illumination. 2. Based on the inner and exterior products of image gradients, gradient correlation and feature vector field are introduced and two novel descriptors, gradient correlation descriptor (GCD) and feature vector descriptor (FVD), are constructed. Both the GCD and FVD are invariant to image rotation as well as to linear change of illumination. In addition, experimental results show that these two descriptors have also a good adaptability to image affine distortion, blurring, JPEG compression and nonlinear change of illumination. 3. Inspired by Harris corner detector, Harris correlation and Harris feature vector field are introduced and two novel descriptors, Harris correlation descriptor (HCD) and Harris feature vector descriptor (HFVD), are proposed. Both the HCD and HFVD are invariant to image rotation as well as to linear change of illumination. In addition, experimental results show also that these two descriptors perform well under image affine transformation, blurring, JPEG compression and nonlinear change of illumination.
shelfnumXWLW1366
Other Identifier200618014628041
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6173
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
王旭光. 图像特征点检测与匹配研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2009.
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