Landry Benoit

On the value of the Kullback---Leibler divergence for cost-effective spectral imaging of plants by optimal selection of wavebands

The practical value of a criterion based on statistical information theory is demonstrated for the selection of optimal wavelength and bandwidth of low-cost lighting systems in plant imaging applications. Kullback–Leibler divergence is applied to the problem of spectral band reduction from hyperspectral imaging. The results are illustrated on various plant imaging problems and show similar results to the one obtained with state-of-the-art criteria. A specific interest of the proposed approach is to offer the possibility to integrate technological constraints in the optimization of the spectral bands selected.

Computer vision under inactinic light for hypocotyl-radicle separation with a generic gravitropism-based criterion

Seedling heterotrophic growth monitoring is done by means of computer vision.A separation of radicle and hypocotyl is performed in inactinic light.This is obtained with a generic criterion based on gravitropism.This allows high-throughput phenotyping equipment for analysis of seeds quality. This article proposes a computer-vision based protocol, useful to contribute to high-throughput automated phenotyping of seedlings during elongation, the stage following germination. Radicle and hypocotyl are two essential organs which start to develop at this stage, with the hypocotyl growing towards the soil surface and the radicle exploring deeper layers for nutrient absorption. Early identification and measurement of these two organs are important to the characterization of the plant emergence and to the prognosis of the adult plant. In normal conditions, this growth process of radicle and hypocotyl takes place in the soil, in the dark. Identification and measurement of these two organs are therefore challenging, because they need to be achieved with no light that could alter normal growth conditions. We propose here an original protocol exploiting an inactinic green light, produced by a controlled LED source, coupled to a standard low-cost gray-level camera. On the resulting digital images, we devise a simple criterion based on gravitropism and amenable to direct computer implementation. The automated criterion, through comparison with the performance of human experts, is demonstrated to be efficient for the detection and separation of radicle and hypocotyl, and generic for various species of seedlings. Our protocol especially brings improvement in terms of cost reduction over the current method found in the recent literature which resorts to higher-cost passive thermal imaging to perform the same task in the dark, and that we also consider here for comparison. Our protocol connected to automation of image acquisition, can serve to improve high-throughput phenotyping equipments for analysis of seed quality and genetic variability.

Information-theoretic modeling of trichromacy coding of light spectrum

Trichromacy is the representation of a light spectrum by three scalar coordinates. Such representation is universally implemented by the human visual system and by RGB (Red Green Blue) cameras. We propose here an informational model for trichromacy. Based on a statistical analysis of the dynamics of individual photons, the model demonstrates a possibility for describing trichromacy as an information channel, for which the input–output mutual information can be computed to serve as a measure of performance. The capabilities and significance of the informational model are illustrated and motivated in various situations. The model especially enables an assessment of the influence of the spectral sensitivities of the three types of photodetectors realizing the trichromatic representation. It provides a criterion to optimize possibly adjustable parameters of the spectral sensitivities such as their center wavelength, spectral width or magnitude. The model shows, for instance, the usefulness of some overlap with smooth graded spectral sensitivities, as observed for instance in the human retina. The approach also, starting from hyperspectral images with high spectral resolution measured in the laboratory, can be used to devise low-cost trichromatic imaging systems optimized for observation of specific spectral signatures. This is illustrated with an example from plant science, and demonstrates a potential of application especially to life sciences. The approach particularizes connections between physics, biophysics and information theory.

3D Multimodal Simulation of Image Acquisition by X-Ray and MRI for Validation of Seedling Measurements with Segmentation Algorithms

In this report, we present a 3D simulator for the numerical validation of segmentation algorithms for seedling in soil from X-ray or MRI. A 3D simulator of root in elongation is coupled to a simulator of the image acquisition to generate images of simulated seedling associated with a known synthetic ground truth. We detail how acquisition parameters of the seedling and parameters of the imaging systems are estimated and combined to produce realistic images. The resulting simulator is available on line to open the possibility of segmentation challenges with in silico validation based on unlimited number of seedling.