主成分分析与广义Hebbian算法在图像压缩与人脸识别中的比较

2006 International Conference on Computer Engineering and Systems Pub Date : 2006-11-01 DOI:10.1109/ICCES.2006.320450

M. Rizk, E. Koosha

{"title":"主成分分析与广义Hebbian算法在图像压缩与人脸识别中的比较","authors":"M. Rizk, E. Koosha","doi":"10.1109/ICCES.2006.320450","DOIUrl":null,"url":null,"abstract":"In this paper we perform image compression and face recognition using principal component analysis (PCA) and the generalized Hebbian algorithm (GHA) which is one of the PCA techniques involving neural network. By implementing the PCA and GHA algorithms for image compression we found that PCA gives better compression ratio to the image than GHA and as for face recognition we found that GHA gives more recognition rate than PCA","PeriodicalId":261853,"journal":{"name":"2006 International Conference on Computer Engineering and Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A Comparison of Principal Component Analysis and Generalized Hebbian Algorithm for Image Compression and Face Recognition\",\"authors\":\"M. Rizk, E. Koosha\",\"doi\":\"10.1109/ICCES.2006.320450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we perform image compression and face recognition using principal component analysis (PCA) and the generalized Hebbian algorithm (GHA) which is one of the PCA techniques involving neural network. By implementing the PCA and GHA algorithms for image compression we found that PCA gives better compression ratio to the image than GHA and as for face recognition we found that GHA gives more recognition rate than PCA\",\"PeriodicalId\":261853,\"journal\":{\"name\":\"2006 International Conference on Computer Engineering and Systems\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Computer Engineering and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCES.2006.320450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Computer Engineering and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES.2006.320450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 9

摘要

本文使用主成分分析(PCA)和广义Hebbian算法(GHA)进行图像压缩和人脸识别，这是一种涉及神经网络的主成分分析技术。通过实现PCA和GHA算法对图像的压缩，我们发现PCA比GHA对图像的压缩比更好，而对于人脸识别，我们发现GHA比PCA的识别率更高

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Comparison of Principal Component Analysis and Generalized Hebbian Algorithm for Image Compression and Face Recognition

In this paper we perform image compression and face recognition using principal component analysis (PCA) and the generalized Hebbian algorithm (GHA) which is one of the PCA techniques involving neural network. By implementing the PCA and GHA algorithms for image compression we found that PCA gives better compression ratio to the image than GHA and as for face recognition we found that GHA gives more recognition rate than PCA

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2006 International Conference on Computer Engineering and Systems

自引率

0.00%

发文量