| 周红,陈忠泽.一种基于LBPV(局部二值模式方差)的指纹分类算法[J].南华大学学报(自然科学版),2017,31(1):57~62.[ZHOU Hong,CHEN Zhong-ze.Fingerprint Classification Based on LBPV(Local binary Pattern Variance)[J].Journal of University of South China(Science and Technology),2017,31(1):57~62.] |
| 一种基于LBPV(局部二值模式方差)的指纹分类算法 |
| Fingerprint Classification Based on LBPV(Local binary Pattern Variance) |
| 投稿时间：2016-11-01 |
| DOI： |
| 中文关键词: 局部二值模式(LBP) K近邻 指纹分类 中心点 |
| 英文关键词:local binary pattern k-nearest neighbor fingerprint classification core point |
| 基金项目: |
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| 中文摘要: |
| 在指纹数据库规模不断增大的情况下,指纹分类对于提高指纹识别的速度和准确率十分重要.本文提出一种利用指纹纹理信息的方法将指纹分为五大类.该方法利用指纹的中心点将指纹模式区分为四个部分并求取每一部分的局部二值模式方差,然后利用K近邻分类器进行分类.实验证明该方法具有良好的分类性能. |
| 英文摘要: |
| In the scale of fingerprint database is increasing,fingerprint classification is crucial for improving the speed and accuracy of fingerprint recognition.This paper presents a method based on the fingerprint texture,and divides the fingerprint image into five categories.According to the core points,a fingerprint image is divided into four regions,each region is modeled with the distribution of the local binary pattern variance (LBPV) values,and then it is classified by KNN classifies.Experiments verify that the method has good classification performance. |
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