Object recognition by multi-spectral imaging with a liquid crystal filter
We describe a spectral-imaging system with a liquid-crystal tunable filter and algorithms for recovering the spectral functions of the illuminant and surface reflectance from the image data. The filter works as a polarization-interference filter with birefringent elements and linear polarizers. We define the camera outputs by a vector equation and describe the spectral functions by a linear model. Then algorithms are presented for estimating the spectral functions from the image data. An effective image-processing algorithm is proposed for highlight extraction and region segmentation. Experimental estimation of the illuminant and spectral reflectances shows the efficiency in measurement and the accuracy in estimation of the spectral functions.