Stereo Spectral Imaging System for Plant Health Characterization

Three-dimensional (3D) measurements of whole plants may provide detailed structure information about plant health and also complement existing X-ray systems for the below-ground part. In addition to this structure characterization of plants, spectral information may also biochemically characterize plants' health. A stereo vision technique is a cost-effective and rapid imaging technique for measuring and reconstructing 3D structures. The Normalized Difference Vegetation Index (NDVI) requiring measurements of two spectral wavelengths at NIR and red spectral regions has been widely used in remote sensing as an index to estimate various vegetation properties including chlorophyll concentration in leaves, leaf area index, biomass, and plant productivity. We integrated both stereo vision and NDVI techniques and developed a stereo spectral imaging (SSI) system for chlorophyll and biomass quantification of plants in 3D space. We used a stereo vision camera system and custom designed a dual-wavelength filter system at 690 nm and 750 nm to develop the SSI system. Calibration techniques for NDVI computation using two spectral band images were developed by referencing a diffuse reflectance panel. We also developed a texture mapping technique for rendering NDVI values in 3D space. In this paper, the performance of the SSI system was evaluated with an artificial plant showing spectral properties similar to green leaves of real plants.