苍蝇翅膀生物识别

2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2013-04-16 DOI:10.1109/CIBIM.2013.6607912

Michael E. Payne, Jonathan Turner, Joseph Shelton, Joshua Adams, J. Carter, Henry Williams, Caresse Hansen, I. Dworkin, G. Dozier

{"title":"苍蝇翅膀生物识别","authors":"Michael E. Payne, Jonathan Turner, Joseph Shelton, Joshua Adams, J. Carter, Henry Williams, Caresse Hansen, I. Dworkin, G. Dozier","doi":"10.1109/CIBIM.2013.6607912","DOIUrl":null,"url":null,"abstract":"Genetic and Evolutionary Feature Extraction (GEFE), introduced by Shelton et al. [1], [2], [3], use genetic and evolutionary computation to evolve Local Binary Pattern (LBP) based feature extractors for facial recognition. In this paper, we use GEFE in an effort to classify male and female Drosophila melanogaster by the texture of their wings. To our knowledge, gender classification of the drosophila melanogaster via its wing has not been performed. This research has the potential to simplify the work of geneticists who work with the drosophila melanogaster. Our results show that GEFE outperforms both LBP and Eigenwing methods in terms of accuracy as well as computational complexity.","PeriodicalId":286155,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fly wing biometrics\",\"authors\":\"Michael E. Payne, Jonathan Turner, Joseph Shelton, Joshua Adams, J. Carter, Henry Williams, Caresse Hansen, I. Dworkin, G. Dozier\",\"doi\":\"10.1109/CIBIM.2013.6607912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Genetic and Evolutionary Feature Extraction (GEFE), introduced by Shelton et al. [1], [2], [3], use genetic and evolutionary computation to evolve Local Binary Pattern (LBP) based feature extractors for facial recognition. In this paper, we use GEFE in an effort to classify male and female Drosophila melanogaster by the texture of their wings. To our knowledge, gender classification of the drosophila melanogaster via its wing has not been performed. This research has the potential to simplify the work of geneticists who work with the drosophila melanogaster. Our results show that GEFE outperforms both LBP and Eigenwing methods in terms of accuracy as well as computational complexity.\",\"PeriodicalId\":286155,\"journal\":{\"name\":\"2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIBIM.2013.6607912\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIBIM.2013.6607912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

遗传和进化特征提取(Genetic and Evolutionary Feature Extraction, GEFE)由Shelton等人[1]，[2]，[3]提出，利用遗传和进化计算进化出基于局部二值模式(Local Binary Pattern, LBP)的特征提取器，用于人脸识别。在本文中，我们试图用GEFE方法根据果蝇翅膀的纹理来对雌雄果蝇进行分类。据我们所知，还没有人通过果蝇的翅膀对其进行性别分类。这项研究有可能简化研究黑腹果蝇的遗传学家的工作。结果表明，GEFE在精度和计算复杂度方面都优于LBP和特征翼方法。

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

Fly wing biometrics

Genetic and Evolutionary Feature Extraction (GEFE), introduced by Shelton et al. [1], [2], [3], use genetic and evolutionary computation to evolve Local Binary Pattern (LBP) based feature extractors for facial recognition. In this paper, we use GEFE in an effort to classify male and female Drosophila melanogaster by the texture of their wings. To our knowledge, gender classification of the drosophila melanogaster via its wing has not been performed. This research has the potential to simplify the work of geneticists who work with the drosophila melanogaster. Our results show that GEFE outperforms both LBP and Eigenwing methods in terms of accuracy as well as computational complexity.

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

2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)

自引率

0.00%

发文量