Mr. JiShi Zheng Profile

JiShi Zheng

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Proceedings Article | 15 August 2023 Paper

Recognition of expiry data on food packages based on deep learning

Junhui Li, Jishi Zheng

Proceedings Volume 12719, 127193Q (2023) https://doi.org/10.1117/12.2685778

KEYWORDS: Optical character recognition, Quantization, Printing, Deep learning, Image segmentation, Visual process modeling, Packaging, Data modeling, Detection and tracking algorithms

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There is a great deal of information on food packaging, including the name of the food, the expiry date and the ingredients. This information, especially the expiration date, needs to be printed correctly before the product is brought to market. Failure to print the correct expiration date can lead to public health problems and recalled products causing financial losses to the company. In this work, we propose an automatic detection and identification of validity areas that can be achieved efficiently and accurately. First, the DBNet network-based approach is applied to detect the expiration date region on food packages. Then the detected expiration date area is intercepted and input to the character recognition network CRNN for character recognition. Finally, the proposed model is deployed on Jetson Xavier NX to implement edge computing of the algorithm, while inference acceleration of the model is performed using TensorRT and FP16 or INT8 quantization. The experimental results show that the method achieves good performance in the detection and identification of expiration dates on different types of food packages, and the method has good real-time and portability.

Proceedings Article | 2 February 2023 Open Access

Design of vehicle log image acquisition system based on deep learning and laser sensor

ShaoYi Li, JiShi Zheng

Proceedings Volume 12462, 1246205 (2023) https://doi.org/10.1117/12.2660793

KEYWORDS: Cameras, Target detection, Sensors, Ranging, Education and training, Detection and tracking algorithms, Image sensors, Image acquisition, Object detection, Image segmentation

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The application of digital image processing technology in log volume gauge count greatly promoted the progress of forestry production to intelligent automation direction. However, based on digital image processing of intelligent log ruler algorithm for accurate ruler, the first premise is to obtain high-definition log end image, under the same log ruler algorithm, image clarity determines the final detection effect of the algorithm system, high-definition picture can improve the accuracy of algorithm recognition. In the natural environment, how to obtain the high-quality image of the log face effectively without changing the resolution of the camera is a problem. This paper presents a method based on the combination of laser ranging sensor and Yolov3 target detection algorithm, and an ZYNQ embedded system for automatic acquisition of higher quality log end face image is designed. Finally, the images obtained by the system are processed into the dense wood detection segmentation algorithm to obtain the log recognition results. Compared with the traditional image acquisition method, the number of logs that can be recognized by the images collected by the system designed in this paper increases by 36.6%. The experimental results show that, the system can obtain clear and higher quality target images in complex environment background and different illumination intensity. The problem of how to obtain high quality log end face image without changing camera resolution in natural environment is solved successfully.

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