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Recognition Using a Multi-Channel Vision System and Its Application

多通道视觉系统识别及其应用

基本信息

批准号：
17500129
负责人：
TOMINAGA S.
金额：
$ 2.18万
依托单位：
Chiba University (2006)Osaka Electro-Communication University (2005)
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2005
资助国家：
日本
起止时间：
2005 至 2006
项目状态：
已结题

项目摘要

We have developed a technique for multi-channel vision system and its application to vision problems. The multi-channel vision system has more than three channels in the visible range of 400-700 nm, different from the fixed system with three channels of RGB. This system is useful for solving several vision problems. First, it improves color resolution of the camera system. Second, the system makes it easy to estimate spectral functions such as spectral-energy distribution of a light source and spectral reflectance of an object surface. The basic system of multi-channel imaging consists of narrowband filters, a monochrome digital camera, and a personal computer.In this research, we first developed systems for multi-channel imaging and algorithms for estimating the spectral information. Next, we developed a system for predicting three-dimensional reflection properties of an object. Moreover, the multi-channel vision system was applied to the following practical problems.(1) We considered an effective method for identifying objects in a natural scene and a method for classifying object materials on a raw circuit board.(2) A method was developed for classifying fluorescent scene illuminant by using a vision system with narrow band filtration. Most fluorescent illuminant spectra can be classified into three groups.(3) A method was devised a method for modeling human skin coloring with foundation makeup and estimating the surface-spectral reflectance by using the Kubelka-Munk theory.(4) We proposed an approach to digital archives of art paintings by using new techniques of computer vision and graphics. The process of digital archiving is decomposed into two stages of image acquisition and image rendering.(5) A method was developed for estimating an omnidirectional distribution of the scene illuminant spectral-power distribution from images taken by a camera aimed at a mirrored ball.

我们开发了一种多通道视觉系统技术及其在视觉问题中的应用。多通道视觉系统在400-700 nm可见范围内具有3个以上通道，不同于固定的RGB 3通道系统。这个系统对解决几个视觉问题很有用。首先，它提高了相机系统的色彩分辨率。其次，该系统可以方便地估计光谱函数，如光源的光谱能量分布和物体表面的光谱反射率。多通道成像的基本系统由窄带滤光片、单色数码相机和个人计算机组成。在这项研究中，我们首先开发了多通道成像系统和估计光谱信息的算法。接下来，我们开发了一个预测物体三维反射特性的系统。此外，将多通道视觉系统应用于以下实际问题。(1)我们考虑了一种自然场景中物体识别的有效方法和一种原始电路板上物体材料分类的方法。(2)提出了一种利用窄带滤波视觉系统对荧光场景光源进行分类的方法。大多数荧光光源光谱可分为三类。(3)设计了一种基于Kubelka-Munk理论的人体皮肤着色建模和表面光谱反射率估算方法。(4)提出了一种利用计算机视觉和图形学新技术实现艺术绘画数字档案的方法。将数字存档过程分解为图像采集和图像绘制两个阶段。(5)提出了一种利用相机对准镜像球拍摄的图像估计场景光源光谱功率全向分布的方法。