Pattern Detection in Gray-Scale Images with Polarization Coding

Abstract

Most of the matched filtering techniques that have been used for pattern recognition have manipulated amplitude and phase information. Light, however, has another principal type of information that has not yet been used for pattern recognition. We propose a matched filtering technique which manipulates the polarization of light and shows the merits of using polarization information. The amplitude transmittance of input images is coded into the two-dimensional orientation distribution of linearly polarized light. A polarization spatial filter, which can change the light polarization two-dimensionally, is designed by considering the polarization distribution of the Fourier transform of an image to be detected which is polarization-coded. The proposed technique shows a better capacity to discriminate gray-scale images than do the conventional matched filtering techniques.