社区车辆通行智能门禁软件系统设计

发布时间：2018-06-24 02:13

本文选题：运动目标检测 + 车牌识别　；参考：《西安科技大学》2016年硕士论文

【摘要】：近年来,科学技术呈现出跳跃式的发展,技术改革日新月异,尤其是计算机和计算机视觉技术的发展,成为当今社会研究中最主要的热点。利用高新技术取代人类活动,解放劳动力,提高生产效率和精度一直是人们致力研究的问题,而人类活动(生产、生活)中信息的交流中,80%左右的信息是视觉信息。车辆通行智能门禁系统是智慧城市的重要内容之一,融合了智能检测、车牌识别以及自动门禁控制系统,是数字图像处理、计算机技术以及自动化技术在实际生活中的一个重要应用。针对社区车辆门禁智能管理系统设计工作的研究,本文主要对其中基于图像处理技术的智能识别与检测部分展开研究,研究工作可以分为成4个部分:车辆通行事件检测、车牌定位、字符分割以及字符识别。首先,车辆通行检测研究中,我们采用了基于运动目标检测的思想,通过背景差分方法对检测区域内的目标进行检测,利用车辆相对于行人、自行车等干扰目标在形状和尺寸等方面的本质差异进行判别得到车辆通行事件的检测结果。在背景建模过程中,我们采用了混合高斯模型来建立模型,进行目标的检测。其次,对于车牌定位技术的研究,车牌定位方面,由于门禁系统应用场景的简单性,在算法设计中更加具有针对性,更加强调车牌的色彩,同时考虑到黑底白字和白底黑字车牌的存在,结合纹理、边缘梯度信息,利用灰度形态学处理技术,设计定位算法。在车牌识别方面,由于本文中门禁系统应用场景简单,车牌图像样本状况较好,对车牌矫正和切割技术要求较低,因此本文中分别采用线性回归方法和垂直投影技术进行车牌矫正和字符切割。然后对于字符识别,我们采用现在最先进的深度学习网络进行字符识别,首先通过深度信度网络模型,建立生成式概率模型,其次将模型展开,构建卷积神经网络模型,进行字符的分类识别。最后,基于matlab仿真平台对系统进行了界面开发设计,将智能门禁系统统一到同一平台,实现人机交互,便于算法研究和同一的管理。
[Abstract]:In recent years, science and technology has been developing by leaps and bounds, and technological reform is changing with each passing day, especially the development of computer and computer vision technology, which has become the most important hot spot in the social research nowadays. Using high and new technology to replace human activities, liberate labor force, improve production efficiency and precision has been a problem that people have been working hard to study, and in the exchange of information in human activities (production, life), about 80% of the information is visual information. The intelligent access control system is one of the important contents of intelligent city. It combines intelligent detection, license plate recognition and automatic access control system. It is a digital image processing system. Computer technology and automation technology in real life an important application. In view of the research on the design of community vehicle access control intelligent management system, this paper mainly studies the intelligent recognition and detection based on image processing technology. The research work can be divided into four parts: vehicle traffic event detection, License plate location, character segmentation and character recognition. First of all, in the research of vehicle traffic detection, we adopt the idea of moving target detection, using the background differential method to detect the target in the area, using the vehicle relative to the pedestrian, The detection results of vehicle traffic events are obtained by discriminating the essential differences in shape and size of interfering targets such as bicycles. In the process of background modeling, we use the mixed Gao Si model to build the model and detect the target. Secondly, for the research of license plate location technology and license plate location, because of the simplicity of the application scene of the access control system, it has more pertinence in the algorithm design and more emphasis on the color of the license plate. At the same time, considering the existence of white characters and black characters on black background, combined with texture and edge gradient information, the location algorithm was designed using grayscale morphology processing technology. In the area of license plate recognition, because of the simple application scene of the entrance control system in this paper, the status of license plate image samples is good, and the requirements for license plate correction and cutting technology are lower. Therefore, linear regression method and vertical projection technique are used to correct license plate and cut characters. Then for character recognition, we use the most advanced depth learning network for character recognition. Firstly, through the depth reliability network model, we establish the generated probability model, and then expand the model to construct the convolution neural network model. Classification and recognition of characters. Finally, the interface of the system is designed based on the matlab simulation platform, and the intelligent access control system is unified into the same platform to realize human-computer interaction, which is convenient for the algorithm research and the management of the same system.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.4;TP311.52

【参考文献】