Recognition Using a Multi-Channel Vision System and Its Application

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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.