Fatma E. Abd El-Sattar, M. Rihan, A. El-Fishawy, Ghada M. El-Banby, Noha A. El-Hag, F. El-Samie, A. Khalaf
{"title":"Fuzzy Enhancement Technique of Face Images","authors":"Fatma E. Abd El-Sattar, M. Rihan, A. El-Fishawy, Ghada M. El-Banby, Noha A. El-Hag, F. El-Samie, A. Khalaf","doi":"10.1109/ICEEM52022.2021.9480650","DOIUrl":null,"url":null,"abstract":"Nowadays, different systems and applications secure personal data using the person's biometric features. Face, fingerprint, hand geometry, palm print, iris, and voice signatures are examples of biometric traits. This paper presents a fuzzy enhancement technique for generating high-contrast and clear face images. Since images are captured in various settings, the output images may have poor quality and low contrast. Evaluation metrics such as entropy, spectral entropy, contrast, average gradient and edge magnitude are used for measuring the performance of the proposed technique. The obtained results are compared with those of the recent enhancement techniques.","PeriodicalId":352371,"journal":{"name":"2021 International Conference on Electronic Engineering (ICEEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Electronic Engineering (ICEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEM52022.2021.9480650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Nowadays, different systems and applications secure personal data using the person's biometric features. Face, fingerprint, hand geometry, palm print, iris, and voice signatures are examples of biometric traits. This paper presents a fuzzy enhancement technique for generating high-contrast and clear face images. Since images are captured in various settings, the output images may have poor quality and low contrast. Evaluation metrics such as entropy, spectral entropy, contrast, average gradient and edge magnitude are used for measuring the performance of the proposed technique. The obtained results are compared with those of the recent enhancement techniques.