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.
出处
《计算机测量与控制》
北大核心
2014年第6期1918-1921,共4页
Computer Measurement &Control
关键词
计算网格
属性嵌套
识别率
辨识
干扰
computational grid
attribute nesting
recognition rate
identification
interference
