改进的ReliefF算法在哈萨克斯拉夫文识别中的应用

摘要

As to character recognition problem in the pattern recognition field,to achieve high efficient feature selection and low redundancy,as well as improve the recognition efficiency,an improved ReliefF feature selection algorithm based Kazakhstan printed Cyrillic character recognition method,which selected Kazakh Cyrillic characters,numbers,and punctuation as main ob-ject for the study,was proposed.A further study on the features of traditional ReliefF feature selection algorithm was carried out,and the feature weight calculation was improved to achieve Re-reliefF feature selection algorithm,and the feature part of the character recognition system was optimized.The improved Re-reliefF feature selection method was applied in Kazakh Cyrillic identification system,and the recognition result of this algorithm was compared with the traditional ReliefF feature selection algorithm.Results demonstrate that this method performs better in terms of running speed and so on in Kazakh Cyrillic charac-ters recognition system.%针对模式识别领域中的文字识别问题,为达到较高的识别效率,去除低冗余,选择并提取高效特征,提出以印刷体哈萨克斯拉夫字符、符号及数字为研究目标的基于改进的ReliefF特征选择算法,用于哈萨克斯拉夫文字的识别;对传统的ReliefF算法的特征权重做进一步改进,提出Re-reliefF算法,对文字识别的特征选择及特征提取部分进行优化.将基于改进的ReliefF特征选择算法用于哈萨克斯拉夫文识别问题,将该算法的识别结果与传统ReliefF特征选择算法进行比较,比较结果表明,该算法在哈萨克斯拉夫文文字识别过程中效果良好,具有运行速度快与运行时间降低等特点.