Symbol recognition system based on 3D stereo vision

With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system.

Flapping wing drones show off their skills

The identification and solution of a major efficiency loss in small flapping wing drones lead to more agile aerobatic maneuvers.

Miniaturized 3D Depth Sensing-Based Smartphone Light Field Camera

The miniaturization of 3D depth camera systems to reduce cost and power consumption is essential for their application in electrical devices that are trending toward smaller sizes (such as smartphones and unmanned aerial systems) and in other applications that cannot be realized via conventional approaches. Currently, equipment exists for a wide range of depth-sensing devices, including stereo vision, structured light, and time-of-flight. This paper reports on a miniaturized 3D depth camera based on a light field camera (LFC) configured with a single aperture and a micro-lens array (MLA). The single aperture and each micro-lens of the MLA serve as multi-camera systems for 3D surface imaging. To overcome the optical alignment challenge in the miniaturized LFC system, the MLA was designed to focus by attaching it to an image sensor. Theoretical analysis of the optical parameters was performed using optical simulation based on Monte Carlo ray tracing to find the valid optical parameters for miniaturized 3D camera systems. Moreover, we demonstrated multi-viewpoint image acquisition via a miniaturized 3D camera module integrated into a smartphone.