Integrated Polarization Analyzing CMOS Image Sensor for Material Classification

Abstract

Material classification is an important application in computer vision. The inherent property of materials to partially polarize the reflected light can serve as a tool to classify them. In this paper, a real-time polarization sensing CMOS image sensor using a wire grid polarizer is proposed. The image sensor consist of an array of 128 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\, \times \,$</tex></formula> 128 pixels, occupies an area of 5 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$\, \times \,$</tex></formula> 4 mm <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$^{2}$</tex></formula> and it has been designed and fabricated in a 180-nm CMOS process. We show that this image sensor 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 achieved by calculating the Fresnel reflection coefficients, the degree of 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. It is also shown that the image sensor can differentiate among various metals by sensing the change in the polarization Fresnel ratio.