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In this study, an efficient algorithm for eye state detection is proposed. At first, a new face detection method is presented for noisy images that finds the face area in the input image well. Then, novel algorithms for detection of eye region and eye state are introduced. The performance of the proposed method is evaluated on four different databases namely FERET, Aberdeen, IMM and CVL which contain more than 5700 images with different descents, positions, light conditions and glasses. The results show that the new method achieves more accuracy rate than the previously presented algorithms, while it does not need training data and is also computationally efficient.<\/jats:p>","DOI":"10.1049\/iet-cvi.2011.0091","type":"journal-article","created":{"date-parts":[[2013,6,7]],"date-time":"2013-06-07T12:03:07Z","timestamp":1370606587000},"page":"184-200","source":"Crossref","is-referenced-by-count":13,"title":["Efficient algorithms for detection of face, eye and eye state"],"prefix":"10.1049","volume":"7","author":[{"given":"Hashem","family":"Kalbkhani","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering Urmia University Urmia Iran"}]},{"given":"Mahrokh G.","family":"Shayesteh","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering Urmia University Urmia Iran"},{"name":"Wireless Research Laboratory ACRI Electrical Engineering Department Sharif University of Technology Tehran Iran"}]},{"given":"Seyyed","family":"Mohsen Mousavi","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering Urmia University Urmia Iran"}]}],"member":"265","published-online":{"date-parts":[[2013,6]]},"reference":[{"key":"e_1_2_8_2_2","doi-asserted-by":"crossref","unstructured":"Tabrizi P.R. 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