Dr. Rui Chen Profile

Dr. Rui Chen

at Xi'an Technological Univ

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Publications (2)

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Proceedings Article | 4 March 2024 Paper

Target recognition and range detection algorithm based on visible-depth image fusion

Wei Su, Rui Chen, Chengbo Ai, Xinyue Liu

Proceedings Volume 13070, 130700L (2024) https://doi.org/10.1117/12.3014594

KEYWORDS: Point clouds, Image fusion, Calibration, LIDAR, Visible radiation, Cameras, Target recognition, RGB color model, Matrices, 3D image processing

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It is necessary to obtain the surrounding information by the sensor to realize target identification and distance detection in the unmanned situational awareness task. The sensors used to collect target information can be divided into visible light band sensors such as visible light cameras and non-visible light wavelength sensors such as Light Detection and Ranging (LiDAR) from the optical characteristics. The LiDAR focuses on acquiring target distance and reflection intensity information, but the details are limited and not conducive to human observation. The visible light cameras focus on acquiring well-structured and detailed target information, but it is difficult to obtain distance information. In this paper, a target recognition method based on visible-depth image fusion for heterogeneous sensors is studied to solve the influence of environmental, spatial and heterogeneous data factors on fusion results. The fusion of point cloud images and visible light image data into visual images incorporating distance information is achieved by employing a combination of the RANSAC algorithm-based spatial line intersection method and the least squares method. And target recognition and distance detection methods based on yolov5s algorithm were studied for fusion data. Through the establishment of dataset and the training of deep learning network, the specific target identification and distance determination are realized. The results show that the specific target recognition rate of this method is greater than 94%, and the accuracy is 2mm (at 10m distance). The results of target recognition and distance determination can be directly sent to the unmanned situation awareness platform to provide a basis for its next decision.

Proceedings Article | 12 December 2018 Paper

Error comparison and analysis of six-light-screen vertical target under different light-screen-array model

Rui Chen, Jin-ping Ni, Ding Chen

Proceedings Volume 10846, 108460A (2018) https://doi.org/10.1117/12.2503301

KEYWORDS: Error analysis, Calibration, Weapons, Instrument modeling, Factor analysis, Sensors, Aerospace engineering, Analytical research, Time metrology, Computer simulations

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Six-light-screen vertical target is an ideal equipment for the projectile flight parameter measurement of the rapid-fire weapon, the light-screen-array model of this kind of equipment is mainly divided into double V shaped and double N shaped, which build different light-screen structure in the space respectively. By recording the time that the projectile reaching each light-screen, and combining with the known spatial structure of the lightscreen array, the flight parameter of projectiles can be measured. Due to the measuring formula is determined by the light-screen-array model, the error influencing factors are considered under different model, and the influence of each factors were analyzed in the selected target plane, respectively. The error distribution were compared under the same condition of each error influencing factors. Then the combined error are calculated and the combined error distribution in the 1m×1m target plane were estimated. The research can provide a useful reference for error analysis in practice, and provide new ideas for improving the measurement precision of rapid-fire weapons.

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