【摘要】 针对路边停车的智能化管理程度较低的问题,以现行标准为依据,对车牌识别面临的问题进行分析。根据所捕获图像的特点,通过高斯滤波、顶帽运算、Otsu算法进行图像预处理,消除噪点,完成背景提取和图像二值化。运用闭运算结合车牌的外形特征完成车牌识别。结合投影法、字符间隔及尺寸的测定和轮廓分析法完成字符分割。最后,提取字符图片的HOG特征,设计了一个基于SVM的字符分类器,实现了一个准确率高、适应性强的车牌识别系统。更多还原

【Abstract】 In response to the low level of intelligent management of on-street parking, the problems faced by license plate recognition are analyzed based on the current standards. According to the characteristics of the captured image, image preprocessing is performed by Gaussian filtering, Top Hat operation and Otsu algorithm to eliminate noise, and background extraction and image binarization are completed. The license plate recognition is completed by using the closed operation combined with the shape features of the license plate. The character segmentation is completed by combining the projection method, the determination of character interval and size, and the contour analysis method. Finally, HOG features of character images are extracted and a character classifier based on SVM is designed to realize a license plate recognition system with high accuracy and high adaptability.更多还原