We demonstrate a wafer-level process for achieving monolithic photonic integration of a light-emitting diode (LED) with a waveguide and photodiode on a GaN-on-silicon platform. Both silicon removal and back-side thinning are conducted to achieve a suspended device architecture. A highly confined waveguide that utilizes the large index contrast between GaN and air is used for the connection between the LED and the photodiode. The suspended waveguide is considered as an in-plane escape cone of the LED, and the photodiode is located at the other end of the waveguide. The photons emitted from the LED are transported to the photodiode through the suspended waveguide parallel to the LED surface, leading to in-plane data transport using visible light. This proof-of-concept monolithic integration paves the way towards in-plane visible light communication as well as photonic computation on a single chip.
Recently, visible light positioning has gradually become a research hotspot in indoor environments. Based on a single transmitter and a single tilted optical receiver, a three-dimensional (3-D) indoor visible light positioning system is proposed. The tilted optical receiver is installed on a rotatable and retractable platform. The 3-D space is divided many two-dimensional (2-D) planes by lifting the platform of the optical receiver. In each 2-D plane, various azimuth angles can be obtained by rotating the receiver platform, which offers a feasible way to perform multiple measurements with different azimuth angles to achieve the angle gain. According to the difference of the angle gain, a 3-D positioning algorithm is proposed. Experimental results show that the proposed positioning algorithm can provide good positioning accuracy.
We present a method for distinguishing human face from high-emulation mask, which is increasingly
used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional
facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the
high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is
used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral
information of the observed face. Experiments show that mask made of silica gel has different spectral
reflectance compared with the human skin. As multispectral image offers additional spectral
information about physical characteristics, high-emulation mask can be easily recognized.
We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive
high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution
using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by
the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by
combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling
method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the
sampled pattern on the SLM with the proposed method.
Homoepitaxial grown InGaN/GaN p-i-n junction was deposited on GaN/Si template with AlN/GaN supperlattice as interlayer by molecular beam epitaxy. Different surface microstructure of the p-GaN was affected by the amount of Mg flux. Light-emitting diode was fabricated from the p-i-n junction. The crystal properties of InGaN/GaN p-i-n junction and the related light-emitting diode properties were investigated.