Moving foreground detection is a very important step for many applications such as human behavior analysis for visual surveillance, model-based action recognition, road traffic monitoring, etc. Background subtraction is a very popular approach, but it is difficult to apply given that it must overcome many obstacles, such as dynamic background changes, lighting variations, occlusions, and so on. In the presented work, we focus on this problem (foreground/background segmentation), using a type-2 fuzzy modeling to manage the uncertainty of the video process and of the data. The proposed method models the state of each pixel using an imprecise and adjustable Gaussian mixture model, which is exploited by several fuzzy classifiers to ultimately estimate the pixel class for each frame. More precisely, this decision not only takes into account the history of its evolution, but also its spatial neighborhood and its possible displacements in the previous frames. Then we compare the proposed method with other close methods, including methods based on a Gaussian mixture model or on fuzzy sets. This comparison will allow us to assess our method’s performance, and to propose some perspectives to this work.

In the present work, the dielectric properties of recycled liquid crystals (LCs) (non-purified, purified, and doped with diamond nanoparticles at 0.05, 0.1, and 0.2 wt%) were investigated. The studied LC mixtures were obtained from industrial recycling of end-of-life LC displays presenting mainly nematic phases. Dielectric measurements were carried out at room temperature on a frequency range from 0.1 to 10⁶ Hz using an impedance analyzer. The amplitude of the oscillating voltage was fixed at 1 V using cells with homogeneous and homeotropic alignments. Results show that the dielectric anisotropy of all purified samples presents positive values and decreases after the addition of diamond nanoparticles to the LC mixtures. DC conductivity values were obtained by applying the universal law of dielectric response proposed by Jonscher. In addition, conductivity of the doped LC mixtures is lower than that of the undoped and non-purified LC.

For several decades, Liquid Crystal Displays (LCDs) have been widely used in televisions, laptops, mobile phones, and other devices. Nowadays, liquid crystals (LCs) represent an important economic value of the recycling system of LCDs. The reuse of these organic molecules could become a profitable basis since it permits to preserve the value of these materials. In this context, the general objective of this work focuses on the recovery of LCs as well as on other valuable materials present in end-of-life LCDs. An orderly, manual LCD dismantling line is put into operation for differentiated recycling of electronic boards, cold cathode lamps that may contain mercury, polymers, metals, and other valuable materials. There is also an extraction line where LCD panels are opened and exposed to an ultrasonically activated organic solvent bath to recover LCs. The resulting solution contains LCs, solvent, organic and inorganic impurities. The LCs mixtures were purified and then characterized mainly by spectroscopic, chromatographic, and thermal techniques. A study of the influence of adding diamond nanoparticles at 0.05, 0.1 and 0.2 wt% to recycled LCs was also performed using dielectric spectroscopy. Dielectric properties of LCs were measured at room temperature, using an impedance analyzer in the frequency range from 0.1 to 10 6 Hz.