{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T15:01:22Z","timestamp":1779116482894,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T00:00:00Z","timestamp":1598227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the National Innovation Cluster R&amp;D program","award":["P0006704_Development of energy saving advanced parts"],"award-info":[{"award-number":["P0006704_Development of energy saving advanced parts"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Image thresholding is one of the fastest and most effective methods of detecting objects in infrared images. This paper proposes an infrared image thresholding method based on the functional approximation of the histogram. The one-dimensional histogram of the image is approximated to the transient response of a first-order linear circuit. The threshold value for the image segmentation is formulated using combinational analogues of standard operators and principles from the concept of the transient behavior of the first-order linear circuit. The proposed method is tested on infrared images gathered from the standard databases and the experimental results are compared with the existing state-of-the-art infrared image thresholding methods. We realized through the experimental results that our method is well suited to perform infrared image thresholding.<\/jats:p>","DOI":"10.3390\/a13090207","type":"journal-article","created":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T10:37:32Z","timestamp":1598265452000},"page":"207","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Fast Image Thresholding Algorithm for Infrared Images Based on Histogram Approximation and Circuit Theory"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3557-2944","authenticated-orcid":false,"given":"Manikanta Prahlad","family":"Manda","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Cheongju University, Cheongju 360764, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hi Seok","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Cheongju University, Cheongju 360764, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.measurement.2017.09.052","article-title":"Performance analysis of image thresholding: Otsu technique","volume":"114","author":"Goh","year":"2018","journal-title":"Meas. 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