属性嵌套计算网格智能算法实现车牌汉字精准识别的设计  

License Plate Character Recognition Accuracy Based on Properties Nested Computing Grid Intelligent Algorithms

作　　者：卓伟[1] 马绍惠[2] 王志华[1] 

机构地区：[1]郑州大学软件学院,郑州450002 [2]河南机电高等专科学校,河南新乡453000

出　　处：《计算机测量与控制》2014年第6期1918-1921,共4页Computer Measurement &Control

摘　　要：设计了环境较差情况下高效精准、辨识汉字的智能车牌识别算法,通过引进属性嵌套计算网格实现了汉字高效辨识的车牌识别算法;算法应用结果表明:算法设计的网格密度与识别率是成正比的,采用的属性嵌套计算网格模型,显著地改进了字符的识别率;将属性计算网格算法与属性嵌套计算网格算法对比可知,采用属性嵌套计算网格算法识别率是98.7%,识别率明显较高;设计算法系统不仅实现了汉字识别的稳定、智能特性,同时表现了抵抗较强外界干扰的特性,这一研究对于智能化汉字识别有明显的借鉴价值。A case of high--precision environment is poor, intelligent character recognition license plate recognition algorithm, through the intro- duction of property nested grid computing to achieve efficient recognition of license plate character recognition algorithm, the algorithm application re- sults showed that ： algorithm design mesh density and recognition rate is proportional ; calculated using the properties of the nested grid model, a signifi- cant improvement of the character recognition rater the attributes and attribute nesting algorithm for computing grid computing grid algorithin compari- son shows, the use of computational grid nested attributes algorithm recognition rate was 98.7 %, significantly higher recognition rate. Design algo- rithms Chinese character recognition system not only to achieve a stable, intelligent features, and strong performance to resist outside interference char- acteristics of intelligent character recognition for this study have significant reference value.

关 键 词：计算网格 属性嵌套 识别率 辨识 干扰 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]