In　order　to　study　the　novel　biometric　of　eyebrow,　this　paper　presents　an　eyebrow　recognition　method　by　comparison　of　feature　strings,　the　basic　idea　of　which　is　to　extract　feature　strings　using　discrete　Fourier　transformation　and　K-means　algorithm,　and　to　recognize　a　given　eyebrow　image　as　the　candidate　person　with　the　minimum　edit　distance　between　their　feature　strings.　It　has　been　shown　that　the　method　can　reach　an　accuracy　of　95.45%　or　100.00%　in　six　experiments　on　a　small-scale　eyebrow　database　taken　from　22　persons.　Therefore,　eyebrow　recognition　may　possibly　apply　to　personal　identification,　which　can　be　valid.