Pan Zheng, Huang Min, Zhu Qibing, Zhao Xin
Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi 214122, China.
Sensors (Basel). 2024 Feb 22;24(5):1401. doi: 10.3390/s24051401.
Rapid detection of fish freshness is of vital importance to ensuring the safety of aquatic product consumption. Currently, the widely used optical detecting methods of fish freshness are faced with multiple challenges, including low detecting efficiency, high cost, large size and low integration of detecting equipment. This research aims to address these issues by developing a low-cost portable fluorescence imaging device for rapid fish freshness detection. The developed device employs ultraviolet-light-emitting diode (UV-LED) lamp beads (365 nm, 10 W) as excitation light sources, and a low-cost field programmable gate array (FPGA) board (model: ZYNQ XC7Z020) as the master control unit. The fluorescence images captured by a complementary metal oxide semiconductor (CMOS) camera are processed by the YOLOv4-Tiny model embedded in FPGA to obtain the ultimate results of fish freshness. The circuit for the YOLOv4-Tiny model is optimized to make full use of FPGA resources and to increase computing efficiency. The performance of the device is evaluated by using grass carp fillets as the research object. The average accuracy of freshness detection reaches up to 97.10%. Moreover, the detection time of below 1 s per sample and the overall power consumption of 47.1 W (including 42.4 W light source power consumption) indicate that the device has good real-time performance and low power consumption. The research provides a potential tool for fish freshness evaluation in a low-cost and rapid manner.
快速检测鱼类新鲜度对于确保水产品消费安全至关重要。目前,广泛使用的鱼类新鲜度光学检测方法面临多重挑战,包括检测效率低、成本高、检测设备体积大以及集成度低等问题。本研究旨在通过开发一种用于快速检测鱼类新鲜度的低成本便携式荧光成像设备来解决这些问题。所开发的设备采用紫外发光二极管(UV-LED)灯珠(365纳米,10瓦)作为激发光源,并采用低成本的现场可编程门阵列(FPGA)板(型号:ZYNQ XC7Z020)作为主控制单元。由互补金属氧化物半导体(CMOS)相机捕获的荧光图像由嵌入在FPGA中的YOLOv4-Tiny模型进行处理,以获得鱼类新鲜度的最终检测结果。对YOLOv4-Tiny模型的电路进行了优化,以充分利用FPGA资源并提高计算效率。以草鱼鱼片为研究对象对该设备的性能进行评估。新鲜度检测的平均准确率高达97.10%。此外,每个样本低于1秒的检测时间以及47.1瓦的总功耗(包括42.4瓦的光源功耗)表明该设备具有良好的实时性能和低功耗。该研究为低成本、快速地评估鱼类新鲜度提供了一种潜在工具。