A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry.

Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion-Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.

Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops.

The stricter legislation within the European Union for the regulation of herbicides that are prone to leaching causes a greater economic burden on the agricultural industry through taxation. Owing to the increased economic burden, research in reducing herbicide usage has been prompted. High-resolution images from digital cameras support the studying of plant characteristics. These images can also be utilized to analyze shape and texture characteristics for weed identification. Instead of detecting weed patches, weed density can be estimated at a sub-patch level, through which even the identification of a single plant is possible. The aim of this study is to adapt the monocot and dicot coverage ratio vision (MoDiCoVi) algorithm to estimate dicotyledon leaf cover, perform grid spraying in real time, and present initial results in terms of potential herbicide savings in maize. The authors designed and executed an automated, large-scale field trial supported by the Armadillo autonomous tool carrier robot. The field trial consisted of 299 maize plots. Half of the plots (parcels) were planned with additional seeded weeds; the other half were planned with naturally occurring weeds. The in-situ evaluation showed that, compared to conventional broadcast spraying, the proposed method can reduce herbicide usage by 65% without measurable loss in biological effect.

Membrane orientation and lateral diffusion of BODIPY-cholesterol as a function of probe structure.

Cholesterol tagged with the BODIPY fluorophore via the central difluoroboron moiety of the dye (B-Chol) is a promising probe for studying intracellular cholesterol dynamics. We synthesized a new BODIPY-cholesterol probe (B-P-Chol) with the fluorophore attached via one of its pyrrole rings to carbon-24 of cholesterol (B-P-Chol). Using two-photon fluorescence polarimetry in giant unilamellar vesicles and in the plasma membrane (PM) of living intact and actin-disrupted cells, we show that the BODIPY-groups in B-Chol and B-P-Chol are oriented perpendicular and almost parallel to the bilayer normal, respectively. B-Chol is in all three membrane systems much stronger oriented than B-P-Chol. Interestingly, we found that the lateral diffusion in the PM was two times slower for B-Chol than for B-P-Chol, although we found no difference in lateral diffusion in model membranes. Stimulated emission depletion microscopy, performed for the first time, to our knowledge, with fluorescent sterols, revealed that the difference in lateral diffusion of the BODIPY-cholesterol probes was not caused by anomalous subdiffusion, because diffusion of both analogs in the PM was free but not hindered. Our combined measurements show that the position and orientation of the BODIPY moiety in cholesterol analogs have a severe influence on lateral diffusion specifically in the PM of living cells.

Seedling discrimination with shape features derived from a distance transform.

The aim of this research is an improvement of plant seedling recognition by two new approaches of shape feature generation based on plant silhouettes. Experiments show that the proposed feature sets possess value in plant recognition when compared with other feature sets. Both methods approximate a distance distribution of an object, either by resampling or by approximation of the distribution with a high degree Legendre polynomial. In the latter case, the polynomial coefficients constitute a feature set. The methods have been tested through a discrimination process where two similar plant species are to be distinguished into their respective classes. The used performance assessment is based on the classification accuracy of 4 different classifiers (a k-Nearest Neighbor, Naive-Bayes, Linear Support Vector Machine, Nonlinear Support Vector Machine). Another set of 21 well-known shape features described in the literature is used for comparison. The used data consisted of 139 samples of cornflower (Centaura cyanus L.) and 63 samples of nightshade (Solanum nigrum L.). The highest discrimination accuracy was achieved with the Legendre Polynomial feature set and amounted to 97.5%. This feature set consisted of 10 numerical values. Another feature set consisting of 21 common features achieved an accuracy of 92.5%. The results suggest that the Legendre Polynomial feature set can compete with or outperform the commonly used feature sets.