{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T16:48:13Z","timestamp":1781974093969,"version":"3.54.5"},"reference-count":83,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Agency for Research and Development (ANID), Chile","award":["1180995"],"award-info":[{"award-number":["1180995"]}]},{"name":"National Agency for Research and Development (ANID), Chile","award":["Graduate scholarship 21161616"],"award-info":[{"award-number":["Graduate scholarship 21161616"]}]},{"name":"National Agency for Research and Development (ANID), Chile","award":["Graduate scholarship 21161631"],"award-info":[{"award-number":["Graduate scholarship 21161631"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we present the architecture of a smart imaging sensor (SIS) for face recognition, based on a custom-design smart pixel capable of computing local spatial gradients in the analog domain, and a digital coprocessor that performs image classification. The SIS uses spatial gradients to compute a lightweight version of local binary patterns (LBP), which we term ringed LBP (RLBP). Our face recognition method, which is based on Ahonen\u2019s algorithm, operates in three stages: (1) it extracts local image features using RLBP, (2) it computes a feature vector using RLBP histograms, (3) it projects the vector onto a subspace that maximizes class separation and classifies the image using a nearest neighbor criterion. We designed the smart pixel using the TSMC 0.35 \u03bcm mixed-signal CMOS process, and evaluated its performance using postlayout parasitic extraction. We also designed and implemented the digital coprocessor on a Xilinx XC7Z020 field-programmable gate array. The smart pixel achieves a fill factor of 34% on the 0.35 \u03bcm process and 76% on a 0.18 \u03bcm process with 32 \u03bcm \u00d7 32 \u03bcm pixels. The pixel array operates at up to 556 frames per second. The digital coprocessor achieves 96.5% classification accuracy on a database of infrared face images, can classify a 150\u00d780-pixel image in 94 \u03bcs, and consumes 71 mW of power.<\/jats:p>","DOI":"10.3390\/s21092901","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T21:25:10Z","timestamp":1619040310000},"page":"2901","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Face Recognition on a Smart Image Sensor Using Local Gradients"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6751-3773","authenticated-orcid":false,"given":"Wladimir","family":"Valenzuela","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier E.","family":"Soto","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0571-9212","authenticated-orcid":false,"given":"Payman","family":"Zarkesh-Ha","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering (ECE), University of New Mexico, Albuquerque, NM 87131-1070, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5033-432X","authenticated-orcid":false,"given":"Miguel","family":"Figueroa","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5994","DOI":"10.1109\/ACCESS.2018.2889996","article-title":"A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification","volume":"7","author":"Rui","year":"2019","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Singh, A.K., and Mohan, A. 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