Neural Network-Powered License Plate Recognition System Design

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

Safer Design and Less Cost Operation for Low-Traffic Long-Road Illumination Using Control System Based on Pattern Recognition Technique

The paper covers analysis and investigation of lighting automation system in low-traffic long-roads. The main objective is to provide optimal solution between expensive safe design that utilizes continuous street lighting system at night for the entire road, or inexpensive design that sacrifices the safety, relying on using vehicles lighting, to eliminate the problem of high cost energy consumption during the night operation of the road. By taking into account both of these factors, smart lighting automation system is proposed using Pattern Recognition Technique applied on vehicle number-plates. In this proposal, the road is sectionalized into zones, and based on smart Pattern Recognition Technique, the control system of the road lighting illuminates only the zone that the vehicles pass through. Economic analysis is provided in this paper to support the value of using this design of lighting control system.

基于图像自动识别的停车场信息管理系统设计

随着科学技术的飞速发展,车辆迅速增加,车辆信息统计管理问题已经成为当前停车场管理的一项重要而紧迫的任务。文章设计了一款停车场信息管理系统,系统以单片机作为核心控制部件,利用车辆自动识别模块检测车辆的进入和驶出状态,结合传感器、警示器、显示器等自动完成车辆的信息采集、录入和显示功能,同时可以进行车辆计费统计管理以及停车场车位信息统计管理,并通过远程通信将信息传送到信息管理中心。该系统实现了停车场信息的智能化管理,契合现实社会需求,具有便捷性、可靠性和高效性。

DNA指纹图谱与数据库管理系统的建立及其应用

本文在计算机上建立ＤＮＡ指纹图和与之对应的生物个体的照片与文字档案，通过抽取ＤＮＡ指纹图的特征向量，用微机图象识别系统来进行图象识别和对象查询．为方便档案的管理，将硬件和软件系统做了合理配置．

基于图像识别技术的车辆管理系统的改进研究

本文在现有车牌识别的基础上加入人脸识别技术,设计出基于图像识别技术的车辆管理系统,即车牌识别确定车辆,人脸识别确定人员,然后将车辆与人员进行信息匹配。

图像识别技术在安全防范系统中的应用

本文通过对图像识别技术在安全防范系统中的应用现状分析,提出在不增加硬件成本的基础上融入图像识别技术及软件支持,能够提高安全防范系统的智能程度和自动化控制能力,为智能建筑的使用者提供更为安全、快捷、舒适的工作生活环境。

基于深度学习的蜜柚果树航拍图像检测

精细化、智慧化是果园管理的必然发展趋势,其中果树位置信息是果园管理的重要数据。为了快速获取井冈蜜柚果树的位置,利用无人机航拍获取蜜柚果园的正射影像,提出了一种用于检测蜜柚果树目标的SSD改进算法。该算法将原SSD算法的主干网络VGG替换为VoVNet,提高了特征提取能力。对样本数据进行了裁剪处理,有效提高了算法检测小目标的能力。实验结果表明,蜜柚果树目标的平均检测精度达到92.6%。

基于疫情防控的校园出入车辆管理系统设计与实现

受当前疫情影响,如何高效、准确地识别检测进出高校的车辆是值得重点研究的问题。文章提出的基于疫情防控的校园出入车辆管理系统采用百度AI的车辆识别技术,对出入校园车辆进行识别,可实现车牌识别、职工车辆自动判别、车位信息可视化以及疫情防控等多种功能,实验结果表明,课题研究的基于疫情防控的校园出入车辆管理系统基本可以满足校园出入车辆管理的需求。

基于智能感知的双头运输车安全管控技术研究

机械设备的安全管控是施工现场安全管理的重要部分。针对盾构隧道内施工环境复杂、障碍物多,双头运输车转向、避障困难,易造成碰撞事故的问题,文章从疲劳驾驶与安全辅助驾驶入手,通过图像识别与环境感知技术,开发了双头运输车疲劳驾驶管控技术和双头运输车主动防撞系统,以提升双头运输车施工过程的安全管控能力,保障隧道内的管片运输安全。