[1]郝其伟 明军.基于KL变换的烟叶信号阈值优化方法[J].计算机技术与发展,2007,(05):8-9.
　HAO Qi-wei,MING Jun.Optimum Method about Threshold of Tobacco Leaf Signals Based on KL Transform[J].,2007,(05):8-9.
点击复制

基于KL变换的烟叶信号阈值优化方法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2007年05期
页码:
8-9
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Optimum Method about Threshold of Tobacco Leaf Signals Based on KL Transform
文章编号:
1673-629X（2007）05-0008-02
作者:
郝其伟 明军
安徽大学电子科学与技术学院
Author(s):
HAO Qi-wei;  MING Jun
School of Electronic Engineering and Information Science, Anhui University
关键词:
相关性; KL变换; 阈值空间
Keywords:
correlation;  KL transform;  threshold space
分类号:
TN911.73
文献标志码:
A
摘要:
物料阈值空间的建立是图像识别的一个关键问题。在分析烟叶特性的基础上，对烟叶三基色信号进行KL变换，消除烟叶信号各元素之间的相关性，经过量化编码后，重新建立烟叶信号的三维阈值空间。与传统的建立阈值空间方法相比，新的阈值空间体积显著减小，有效地提高了烟叶检测和分级的精度。该方法简单方便，同样适用其它具有相关特性的物料的识别
Abstract:
Constructing the threshold space of materials is an important problem in image recognition. On analyzing the characteristic of tobacco leaves, KL transform is performed on tobacco leaf signals to remove the correlation between each signal dement. A new threshold space is created after quantification and coding. Comparing with the traditional method, the volume of the new threshold space is noticeably minished. As a result, the precision of examining and classifying tobacco leaves is improved. This method is also suitable to recognizing other materials having the characteristic of correlation because of its simplicity

相似文献/References:

[1]张家柏 王小玲.基于聚类和二进制PSO的特征选择[J].计算机技术与发展,2010,(06):25.
　ZHANG Jia-bai,WANG Xiao-ling.A Novel Algorithm Based on K-Means Clustering and Binary Particle Swarm Optimization[J].,2010,(05):25.
[2]刘忠艳 周波 车向前.一种高效的图像匹配算法[J].计算机技术与发展,2009,(04):45.
　LIU Zhong-yan,ZHOU Bo,CHE Xiang-qian.An Effective Algorithm for Image Registration[J].,2009,(05):45.
[3]李泽军 曾利军 刘文华.基于相关性和语义相似度融合的查询扩展方法[J].计算机技术与发展,2010,(09):66.
　LI Ze-jun,ZENG Li-jun,LIU Wen-hua.Query Expansion Method Based on Relativity and Similarity Inosculate[J].,2010,(05):66.
[4]盛朝强 王君.煤矿井下人员签到系统人脸识别算法研究[J].计算机技术与发展,2012,(07):171.
　SHENG Chao-qiang,WANG Jun.Face Recognition Algorithms of Sign-in System for Underground Coalmine[J].,2012,(05):171.
[5]方承志 刘洁 王坦.无线局域网中基于响应相关性的Turbo译码研究[J].计算机技术与发展,2012,(12):215.
　FANG Cheng-zhi,LIU Jie,WANG Tan.Research on Turbo Decoding Based on Response Correlation in WLAN[J].,2012,(05):215.
[6]张子敬,霍家道.基于 H.264的帧内自适应预测算法[J].计算机技术与发展,2013,(01):83.
　ZHANG Zi-jing,HUO Jia-dao.An Adaptive Prediction Intra-frame Algorithm Based on H. 264[J].,2013,(05):83.
[7]谭文安[][],查安民[],陈森博[]. 优化粒子群的云计算任务调度算法[J].计算机技术与发展,2016,26(07):6.
　TAN Wen-an[]],ZHA An-min[],CHEN Sen-bo[]. Task Scheduling Algorithm of Cloud Computing Based on Particle Swarm Optimization [J].,2016,26(05):6.
[8]段菊,于治国.云环境下基于相关性的并行任务调度策略[J].计算机技术与发展,2018,28(06):178.[doi:10.3969/ j. issn.1673-629X.2018.06.040]
　DUAN Ju,YU Zhi-guo.Parallel Tasks Scheduling Strategy Based on Correlation under Cloud Environment[J].,2018,28(05):178.[doi:10.3969/ j. issn.1673-629X.2018.06.040]
[9]胡荣辉,王瑞通. 云环境下虚拟机集群迁移策略研究[J].计算机技术与发展,2017,27(11):33.
　HU Rong-hui,WANG Rui-tong. Study on Virtual Cluster Migration Strategy in Cloud Environment[J].,2017,27(05):33.
[10]于文静,余洁,徐凌宇.海表面温时间序列的相关性及复杂性研究[J].计算机技术与发展,2019,29(02):181.[doi:10．3969/j．issn．1673－629X．2019．02．038]
　YU Wenjing,YU Jie,XU Lingyu.Research on Correlation and Complexity of Sea Surface Temperature Time Series[J].,2019,29(05):181.[doi:10．3969/j．issn．1673－629X．2019．02．038]

备注/Memo

备注/Memo:
安徽省教育厅重点基金资助项目（2006KJ014A）郝其伟（1982-），男，安徽人，硕士研究生，研究方向为视频处理；明军，教授，硕士生导师，研究方向为视频处理
更新日期/Last Update: 1900-01-01