Affine transformed image matching using Hough transformed planes

使用霍夫变换平面的仿射变换图像匹配

• 批准号: 09680364
• 负责人: NOMURA Yoshihiko
• 金额: $ 0.7万
• 依托单位: Mie University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1997
• 资助国家: 日本
• 起止时间: 1997 至 1998
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-09680364/
• 关键词: Hough Transform; Affine Transform; Gabor Transform; Image; Matching

Searching objects within an image is an important technology in computer vision. In model-based matching system, the appearance of the target-object in an image can be greatly different with the aspect and scale of the model, because of the rotation and translation between the views of the model and the real image. Furthermore if the background of the input image is unknown or with clutters, the matching process will be further complicated. This work presents an efficient method to search a target-object in an image with unknown scene by using the Hough Transform and the Gabor transform. In the latter, spectra information of the input image can be obtained by applying the Gabor transform to the input image. The spectra information has the following characteristics.(1)Each Gabor function is expanded in the frequency domain. Therefore, few Gabor functions could cover whole the frequency spectrum of the original image. This mean it provides very few numbers of features, resulting in the highly efficient calculation.(2) Responding to the rotations of model, the spectra plane rotates.(3) Responding to the scale changes of model, the spectra plane changes its scale while changing its magnitude with constant rate. Using the second and the third characteristics, target-object can be correctly detected and the pose is also calculated by spectra matching. The approach consists of four steps.(1) Amplitude spectra of Gabor-expansion coefficients are calculated at a central pixel on the model image and at all pixels on the scene image.(2) Amplitude spectra are deformed by a log-polar sampling.(3) Considering the effect of rotation and scale change, as an affine-invariant concentric feature, amplitude spectra of Fourier-expansion coefficients are calculated for all the log-polar sampled spectra.(4) A specific pixel having the same Fourier amplitude spectrum as the model image is found out among the pixels on the scene image. The target object is considered to be at the pixel.

在图像中搜索目标是计算机视觉中的一项重要技术。在基于模型的匹配系统中，由于模型视图与真实的图像之间的旋转和平移，目标对象在图像中的外观会随着模型的长宽比和比例而发生很大的变化。此外，如果输入图像的背景是未知的或具有杂波，则匹配过程将进一步复杂化。提出了一种利用Hough变换和Gabor变换在未知场景图像中搜索目标的有效方法。在后者中，可以通过对输入图像应用Gabor变换来获得输入图像的光谱信息。光谱信息具有以下特征。（1）将每个Gabor函数在频域中展开。因此，很少的Gabor函数可以覆盖整个频谱的原始图像。这意味着它提供的特征数量非常少，从而实现了高效的计算。(2)响应于模型的旋转，谱平面也随之旋转。(3)响应于模型尺度的变化，谱面尺度变化的同时，幅值也以恒定速率变化。利用第二和第三特征，可以正确地检测出目标物体，并通过光谱匹配计算出目标物体的位姿。该方法包括四个步骤。(1)在模型图像上的中心像素和场景图像上的所有像素处计算Gabor展开系数的幅度谱。(2)通过对数极坐标采样使振幅谱变形。(3)考虑旋转和尺度变化的影响，作为一个仿射不变的同心特征，傅里叶展开系数的幅度谱计算的所有对数极坐标采样的频谱。(4)在场景图像上的像素中找出具有与模型图像相同的傅立叶振幅谱的特定像素。目标对象被认为是在像素处。