A Method for Estimating Fluorescence Emission Spectra from Image Data of Plant Grain and Leaves Without a Spectrometer

Abstract

This study proposes a method for estimating fluorescence emission spectra from images of plant grain and leaves without using a spectrometer. We construct two types of multiband imaging systems with six channels using ordinary off-the-shelf cameras and UV light. A mobile phone camera is used to detect fluorescence emission in the blue wavelength region for rice grains. For plant leaves, a small monochrome camera is used with additional optical filters to detect chlorophyll fluorescence in the red to far-red wavelength region. A ridge regression approach is used to obtain a reliable estimate of the spectral distribution of the fluorescence emission from the acquired image data. The spectral distribution can be estimated by optimally selecting the ridge parameter without statistically analyzing the fluorescence spectra. An algorithm for optimal parameter selection is developed using a cross-validation technique. In the experiments using real rice grains and green leaves, the estimated fluorescence emission spectral distributions are compared to direct measurement by a spectroradiometer and estimation by the minimum norm estimation method. The reliability of the proposed estimation method is demonstrated.

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