Artificial neuromorphic devices are considered the key component in realizing energy-efficient and brain-inspired computing systems. For the artificial neuromorphic devices, various material candidates and device architectures have been reported, including two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskite materials. In addition to conventional electrical neuromorphic devices, optoelectronic neuromorphic devices, which operate under a light stimulus, have received significant interest due to their potential advantages such as low power consumption, parallel processing, and high bandwidth. This article reviews the recent progress in optoelectronic neuromorphic devices using various active materials such as two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskites

A machine vision inspection system consists of a camera, optics, illumination, and image acquisition system. Especially a scanning system has to be made to measure a large inspection area. Therefore, a machine vision line scan camera needs a line scan light source. A line scan light source should have a high light intensity and a uniform intensity distribution. In this paper, an offset calibration and slope calibration methods are introduced to obtain a uniform light intensity profile. Offset calibration method is to remove the deviation of light intensity among channels through adding intensity difference. Slope calibration is to remove variation of light intensity slope according to the control step among channels through multiplying slope difference. We can obtain an improved light intensity profile through applying offset and slope calibration simultaneously. The proposed method can help to obtain clearer image with a high precision in a machine vision inspection system.

A machine vision inspection system consists of a camera, optics, illumination, and image acquisition system. The illumination system among these uses LED lighting source. Therefore, the driving method of LED lighting source is very important. The two main driving methods of LED lighting system for machine vision are Pulse Width Modulation (PWM) control driving and strobe control driving. PWM control driving method has problems such as a temperature rising of LED and a flickering in image measurement for inspection. On the other hand, strobe control driving method has a difficulty in the control of light intensity because of too short on-time. In this study, we propose a new hybrid-dimming control driving method for LED lighting source for machine vision. The proposed new hybrid-dimming control driving method can control current intensity and current on-time simultaneously so that it can extract clearer images with a high precision without the light saturation of image.

The machine vision technology has been widely used in the industrialized nations like the United States, Japan, and EU in the various industries from the late 1980s. Machine vision inspection system mainly consists of a camera, optics, illumination and an image acquisition system. Optimization of the illumination light source is very important. This paper shows a comparison between Pulse Width Modulation (PWM) control and strobe control in driving LED lighting system for machine vision. PWM control method has problems such as a temperature rising of LED and a flickering in image measurement for inspection. In contrast, the proposed strobe control method can suppress the temperature of LED light source below 40℃. Also, it can remove the flickering problem through a synchronization between a frame grabber and a camera shutter. Finally, the strobe control method was shown to extract clearer images with a high precision compared to PWM control method.