{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:19:34Z","timestamp":1760235574203,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,15]],"date-time":"2021-09-15T00:00:00Z","timestamp":1631664000000},"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 this work, we present an eye-image acquisition device that can be used as an image acquisition front-end application in compact, low-cost, and easy-to-integrate products for smart-city access control applications, based on iris recognition. We present the advantages and disadvantages of iris recognition compared to fingerprint- or face recognition. We also present the main drawbacks of the existing commercial solutions and propose a concept device design for door-mounted access control systems based on iris recognition technology. Our eye-image acquisition device was built around a low-cost camera module. An integrated infrared distance measurement was used for active image focusing. FPGA image processing was used for raw-RGB to grayscale demosaicing and passive image focusing. The integrated visible light illumination meets the IEC62471 photobiological safety standard. According to our results, we present the operation of the distance-measurement subsystem, the operation of the image-focusing subsystem, examples of acquired images of an artificial toy eye under different illumination conditions, and the calculation of illumination exposure hazards. We managed to acquire a sharp image of an artificial toy eye sized 22 mm in diameter from an approximate distance of 10 cm, with 400 pixels over the iris diameter, an average acquisition time of 1 s, and illumination below hazardous exposure levels.<\/jats:p>","DOI":"10.3390\/s21186185","type":"journal-article","created":{"date-parts":[[2021,9,15]],"date-time":"2021-09-15T12:00:44Z","timestamp":1631707244000},"page":"6185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Image Acquisition Device for Smart-City Access Control Applications Based on Iris Recognition"],"prefix":"10.3390","volume":"21","author":[{"given":"Damjan","family":"Zadnik","sequence":"first","affiliation":[{"name":"Iretec d.o.o., 4000 Kranj, Slovenia"}]},{"given":"Andrej","family":"\u017demva","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.optlaseng.2019.06.011","article-title":"High-accuracy multi-camera reconstruction enhanced by adaptive point cloud correction algorithm","volume":"122","author":"Chen","year":"2019","journal-title":"Opt. 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