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摘要本次实验的题目是基于黑背景的交通信号灯检测方法研究，其对汽车行驶过程中闯红灯的检测起到至关重要的作用，对车辆行驶安全有重大的意义。
随着交通公路的发展以及车辆速度的增长，闯红灯的现象屡见不鲜。因此本实验研究出了一种能够在车辆行驶过程中对交通红绿灯检测的算法。由于车辆的震动和光照、噪声等因素会使采集到的图像模糊不清从而影响算法的准确性。因此本次实验需要对实验进行图像处理从而达到算法的稳健性。图像处理是对图像进行加工、分析，使其满足视觉的、心理以及其他要求的技术。本次实验先对采集到的图像进行预处理，随后对预处理的图像进行边框平滑处理。处理当中尽量不让处理过后的图像失真，最后对处理得到的图像标记各个区域并检测是否为圆形来达到检测红绿灯位置的信息。64191
毕业论文关键词：交通灯，图像处理，红绿灯检测，算法的稳健性
毕业设计外文摘要
Title Traffic signal detection method based on black background analysis research
Abstract
The topic of this experiment is based on black background traffic signal detection method research, the car driving through a red light test play a crucial role in the process of, of great significance for vehicle safety.
With the development of highway transportation and the growth of the vehicle speed, the phenomenon of red light. This experimental study out a can of traffic lights in the process of vehicle detection algorithm. Because the vehicle's vibration and noise factors such as light, can make the collected images blurred so as to affect the accuracy of the algorithm. Therefore this experiment need to image processing experiments so as to achieve robustness of the algorithm. Image processing is image processing and analysis, make its can satisfy the demands of visual, psychological, and other technology. This experiment was carried out on the collected images first pretreatment, then to border smoothing preprocessing the image. After the treatment of tries not to let the image distortion, and finally to processing the image tag in different regions and detection for circular to achieve traffic light location information.
Keywords The traffic light, robustness, image processing, target object detection
Key words: traffic lights, image processing, traffic detection, the algorithm robustness
目 次
第1章 绪论 2
1.1选题意义及背景 2
1.2红绿灯视频信息检测技术应用现状 2
1.3技术的未来发展趋势 3
1.4课题实验的主要工作 4
第2章 本次课题实验的总体设计方案和分析 5
2.1总体设计分析 5
2.2总体设计方案 8
第3章 对实验图像的的图像处理 10
3.1概述 10
3.2交通图像分割原理步骤 10
3.2.1预处理方案步骤 11
3.2.2 实验结果 12
3.2.3实验结果分析 15
3.2.4红绿灯图像的分离 15
3.2.5 实验结果 16
3.2.6 实验结果分析 17
3.3红绿灯图像分离原理步骤