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机构地区:[1]上海交通大学计算机科学与工程系
出 处:《上海交通大学学报》1998年第10期1-3,9,共4页Journal of Shanghai Jiaotong University
基 金:国防预研基金
摘 要:针对汽车图象的复杂背景和多变的光照条件,提出了一种用于汽车图象的字符目标提取算法.该算法采用了基于边缘分析的二值化算法结合自适应的形态滤波方法.对字符图象的灰度和纹理分布进行了分析,设计了一种基于一维边缘分析的二值化方法,与其他传统分析方法比较,该方法在运算速度和抗干扰能力上有明显优势.在对二值化图象进行分割时,不采用固定形态滤波结构元素,而是根据子域及其邻域关系自适应地调整用于滤波的结构元素,更有效地提取目标区域.为提高运算速度,还采用了降维的快速算法.经测试,此方法对不同环境和不同光照条件有较强的自适应能力,其定位准确率及实时处理能力都达到了实用标准.An algorithm applied to character extraction of vehicle image is introduced. In regard to the complicated background of vehicle image and the variety of illuminating conditions, it combined a binarization method based on one dimensional edge detection with an adaptive morphological filtering method. The binarization method is based on one dimensional edge detection to effectively utilize the gray scale and texture feature of the character images. It is much more robust and faster than the traditional thresholding methods and edge detecting operator methods. The morphological filtering method is different from the common ones in that its elements is not fixed sized but adaptive to the sub domain and neighborhood, in order to effectively extract the targets. A dimension diminishing method is also used to accelerate the morphological filtering process. Having been used in some automatic tolling systems, the algorithm is proved to be adaptive to various environments and illuminations, and achieves accuracy and processing speed competence for real time applications.
关 键 词:图象处理 交通管理 汽车牌照 字符目标 提取算法
分 类 号:U491[交通运输工程—交通运输规划与管理] TP391.41[交通运输工程—道路与铁道工程]
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