{"title":"Strengthening surf descriptor with discriminant image filter learning: application to face recognition","authors":"Hamdi Jamel Bouchech, S. Foufou, M. Abidi","doi":"10.1109/ICM.2014.7071825","DOIUrl":"https://doi.org/10.1109/ICM.2014.7071825","url":null,"abstract":"Face recognition in extreme situations is still challenging to researchers. While several algorithms have shown great recognition results in ideal conditions, accuracy decreases when recognition tasks present a high illumination variation. In this paper, we propose to add two components to the recognition system to make the surf descriptor efficient in such extreme situations. First, we learn a discriminant image filter that maximizes the discrimination of surf. Second, the obtained discriminant SURF(d-surf) is further strengthened by using multispectral images instead of broad band images. DSURF and multispectral d-surf (MD-SURF) were evaluated against two face databases: the feret database, which served as a benchmark, and the iris-m3 multispectral face database, which presented sun lighted faces. Our algorithms have been evaluated against three state-of-the-art algorithms that are MBLBP, HGPP and LGBPHS. The results validated the superiority of D-SURF over the traditional surf descriptor, while MD-SURF performed best out of all studied algorithms.","PeriodicalId":107354,"journal":{"name":"2014 26th International Conference on Microelectronics (ICM)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134291746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}