{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:21:49Z","timestamp":1763202109304,"version":"build-2065373602"},"reference-count":77,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2017,12,17]],"date-time":"2017-12-17T00:00:00Z","timestamp":1513468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user\u2019s eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.<\/jats:p>","DOI":"10.3390\/s17122933","type":"journal-article","created":{"date-parts":[[2017,12,19]],"date-time":"2017-12-19T03:54:32Z","timestamp":1513655672000},"page":"2933","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Noisy Ocular Recognition Based on Three Convolutional Neural Networks"],"prefix":"10.3390","volume":"17","author":[{"given":"Min","family":"Lee","sequence":"first","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Hyung","family":"Hong","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Kang","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3095","DOI":"10.3390\/s140203095","article-title":"Finger-vein image enhancement using a fuzzy-based fusion method with gabor and retinex filtering","volume":"14","author":"Shin","year":"2014","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"16866","DOI":"10.3390\/s150716866","article-title":"Nonintrusive finger-vein recognition system using NIR image sensor and accuracy analyses according to various factors","volume":"15","author":"Pham","year":"2015","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9248","DOI":"10.3390\/s130709248","article-title":"Retinal identification based on an improved circular gabor filter and scale invariant feature transform","volume":"13","author":"Meng","year":"2013","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4324","DOI":"10.3390\/s120404324","article-title":"Integrating iris and signature traits for personal authentication using user-specific weighting","volume":"12","author":"Viriri","year":"2012","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1109\/34.244676","article-title":"High confidence visual recognition of persons by a test of statistical independence","volume":"15","author":"Daugman","year":"1993","journal-title":"IEEE Trans. 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