Definition of spectrum by colors metamerism using images of plants by ordinary camera

Abstract

In several cases, studying biological objects requires spectral analysis to conduct research. Determination of a spectrum from RGB image data is a highly complex task because image color is formed by mixing colors. The inverse transformation of RGB color-to-spectrum does not have a unique solution. Consequently, this paper proposes an approach based on color deconvolution usage. RGB values are determined and set for each wavelength in the spectrum. Obtained values establish and settle the direction of the axis in the color space closest to the color of the respective wavelength, that is defined from color metamerism in RGB space. Accordingly, a new base of vectors is constructed along which deconvolution is performed. This procedure allows to define color components from the image fragment as a bin of a specific spectrum wavelength. The intensity of bins in the spectrum is found through the distribution of mean intensity for such images. The proposed approach makes it possible to obtain satisfactory results to determine the color of plants for monitoring tasks. Additionally, this method can also be employed as initial data to train a neural network for scrutinizing plant diseases in remote monitoring methods.