摘要
图像匹配是图像处理和计算机视觉领域的一个基础问题,它源自多个方面的实际问题.点特征匹配的首要任务就是提取稳定的特征,并进行描述.该特征能对旋转、尺度缩放、仿射变换、视角变化、光照变化等图像变化因素保持一定的不变性,而对物体运动、遮挡、噪声等因素也保持较好的可匹配性.提出一种基于点的尺度、旋转不变特征变换(SIFT)算法的亚像素级图像配准算法,首先在尺度空间进行特征检测,并确定关键点的位置和关键点所处的尺度,然后使用关键点邻域梯度的主方向作为该点的方向特征,以实现算子对尺度和方向的无关性.该方法具有旋转、尺度缩放、亮度变化不变性,对视角变化、仿射变换、噪声也保持一定程度的稳定.独特性好,信息量丰富,适用于在海量特征数据库中进行快速、准确的匹配.高速性,该匹配算法可以达到实时的要求.
Image matching is a basis in the image processing and computer vision field,it comes from a number of practical problems.The primary task of Point feature matching is to extract the stability features,and to describe them.These features can maintain certain invariance to the image changes factors,such as rotation,zoom scale,affine transformations,and perspective changes,light changes etc.,to the object movement,occlusion,noise and other factors can also maintain good matching.A point-based scale and rotation invariant feature transform algorithm for the sub-pixel image registration is proposed.First of all the feature detection and identification are made in the scale space,the position and scale of key points are determined,and then use main direction of the neighborhood＇s gradient as the direction of the key point in order to achieve the independence of the operator of the scale and direction.The method is invariance to rotation,scale scaling and brightness changes,else maintaining a certain degree of stability to changes of perspective,affine transformation and noise.It is unique,informative and suitable for fast and accurate matching in the mass characteristics database.Being high-speed,the matching algorithm can achieve real-time requirements.
出处
《光电技术应用》
2010年第3期72-74,80,共4页
Electro-Optic Technology Application
基金
国家自然科学基金(10871203)
