{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T04:10:17Z","timestamp":1768709417321,"version":"3.49.0"},"reference-count":33,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,17]],"date-time":"2021-06-17T00:00:00Z","timestamp":1623888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["Finance Code 001"],"award-info":[{"award-number":["Finance Code 001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work proposes a high-throughput implementation of the Otsu automatic image thresholding algorithm on Field Programmable Gate Array (FPGA), aiming to process high-resolution images in real-time. The Otsu method is a widely used global thresholding algorithm to define an optimal threshold between two classes. However, this technique has a high computational cost, making it difficult to use in real-time applications. Thus, this paper proposes a hardware design exploiting parallelization to optimize the system\u2019s processing time. The implementation details and an analysis of the synthesis results concerning the hardware area occupation, throughput, and dynamic power consumption, are presented. Results have shown that the proposed hardware achieved a high speedup compared to similar works in the literature.<\/jats:p>","DOI":"10.3390\/s21124151","type":"journal-article","created":{"date-parts":[[2021,6,17]],"date-time":"2021-06-17T11:20:26Z","timestamp":1623928826000},"page":"4151","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Fully Parallel Implementation of Otsu Automatic Image Thresholding Algorithm on FPGA"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8498-3571","authenticated-orcid":false,"given":"Wysterl\u00e2nya K. P.","family":"Barros","sequence":"first","affiliation":[{"name":"Laboratory of Machine Learning and Intelligent Instrumentation, nPITI\/IMD, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8442-3291","authenticated-orcid":false,"given":"Leonardo A.","family":"Dias","sequence":"additional","affiliation":[{"name":"Centre for Cyber Security and Privacy, School of Computer Science, University of Birmingham, Birmingham B15 2TT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7536-2506","authenticated-orcid":false,"given":"Marcelo A. C.","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Laboratory of Machine Learning and Intelligent Instrumentation, nPITI\/IMD, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil"},{"name":"Department of Computer and Automation Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Barros, W.K., Morais, D.S., Lopes, F.F., Torquato, M.F., Barbosa, R.d.M., and Fernandes, M.A. (2020). Proposal of the CAD system for melanoma detection using reconfigurable computing. 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