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[HS)]

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。

Abstract:

A case of high-precision environment is poor, intelligent character recognition license plate recognition algorithm, through the introduction of property nested grid computing to achieve efficient recognition of license plate character recognition algorithm, the algorithm application results showed that:algorithm design mesh density and recognition rate is proportional; calculated using the properties of the nested grid model, a significant improvement of the character recognition rate; the attributes and attribute nesting algorithm for computing grid computing grid algorithm comparison shows, the use of computational grid nested attributes algorithm recognition rate was 98.7%, significantly higher recognition rate. Design algorithms Chinese character recognition system not only to achieve a stable, intelligent features, and strong performance to resist outside interference characteristics of intelligent character recognition for this study have significant reference value.