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利用CMOS偏振传感器的材料分类

Material Classification Using CMOS Polarization Sensor
加工时间:2013-12-29 信息来源:科技报告(Other) 索取原文[28 页]
关键词:传感器;CMOS;偏振
摘 要:Material classification is an important application in computer vision. The ability to detect the nature of the object surface from image data has a very high potential for applications ranging from low-level inspection to high-level object recognition. The inherent property of materials to partially polarize the reflected light can serve as a tool to classify them. In this chapter, an introduction to material classification is presented in section 5.1. The theory behind polarization upon specular reflection and Fresnel coefficients is covered in section 5.2. The Fresnel reflectance model is also briefly described. The polarized nature of the transmitted light can be used to differentiate between metal and dielectric surfaces in real time due to the different nature in partially polarizing the specular and diffuse reflection components of the reflected light. This is elaborated in section 5.3 by measuring the transmitted irradiance after reflection from the material surface which allows computation of Fresnel reflection coefficients, the degree of partial polarization and the variations in the maximum and minimum transmitted intensities for varying specular angle of incidence. Differences in the physical parameters for various metal surfaces result in different surface reflection behavior, influencing the Fresnel reflection coefficients. Section 5.4, shows that it is possible to differentiate among various metals of varying conductivity by sensing the change in the Polarization Fresnel Ratio and the degree of polarization of the light reflected. Section 5.5 presents a short summary of the methods used to differentiate among material surfaces.
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