{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:12:23Z","timestamp":1763748743540,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T00:00:00Z","timestamp":1662508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2020YFC1511601","32171797"],"award-info":[{"award-number":["2020YFC1511601","32171797"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2020YFC1511601","32171797"],"award-info":[{"award-number":["2020YFC1511601","32171797"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Smoke is an early visual phenomenon of forest fires, and the timely detection of smoke is of great significance for early warning systems. However, most existing smoke detection algorithms have varying levels of accuracy over different distances. This paper proposes a new smoke root detection algorithm that integrates the static and dynamic features of smoke and detects the final smoke root based on clustering and the circumcircle. Compared with the existing methods, the newly developed method has a higher accuracy and detection efficiency on the full scale, indicating that the method has a wider range of applications in the quicker detection of smoke in forests and the prevention of potential forest fire spread.<\/jats:p>","DOI":"10.3390\/s22186748","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6748","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Full-Scale Fire Smoke Root Detection Based on Connected Particles"],"prefix":"10.3390","volume":"22","author":[{"given":"Xuhong","family":"Feng","sequence":"first","affiliation":[{"name":"School of Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5412-5202","authenticated-orcid":false,"given":"Pengle","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Nature Conservation, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction, and Environmental Engineering, North Dakota State University, Fargo, ND 58102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"key":"ref_1","unstructured":"Botto-Tobar, M., Cruz, H., and D\u00edaz Cadena, A. (2021). Machine Learning and Color Treatment for the Forest Fire and Smoke Detection Systems and Algorithms, A Recent Literature Review BT\u2014Artificial Intelligence, Computer and Software Engineering Advances, Springer International Publishing."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s10694-020-01064-z","article-title":"Machine Vision Based Fire Detection Techniques: A Survey","volume":"57","author":"Geetha","year":"2021","journal-title":"FIRE Technol."},{"key":"ref_3","first-page":"159","article-title":"Forest fire detection and identification using image processing and SVM","volume":"15","author":"Mahmoud","year":"2019","journal-title":"J. Inf. Process. Syst."},{"key":"ref_4","first-page":"40","article-title":"Forest Fire Smoke Video Detection Using Spatiotemporal and Dynamic Texture Features","volume":"2015","author":"Zhao","year":"2015","journal-title":"JECE"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"35887","DOI":"10.1007\/s11042-020-09870-x","article-title":"Video smoke detection base on dense optical flow and convolutional neural network","volume":"80","author":"Wu","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_6","first-page":"557","article-title":"Algorithm for detection of fire smoke in a video based on wavelet energy slope fitting","volume":"16","author":"Zhang","year":"2020","journal-title":"J. Inf. Process. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Vijayalakshmi, S.R., and Muruganand, S. (2017, January 19\u201320). Smoke detection in video images using background subtraction method for early fire alarm system. Proceedings of the 2017 2nd International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India.","DOI":"10.1109\/CESYS.2017.8321258"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Tang, T., Dai, L., and Yin, Z. (2017, January 24\u201325). Smoke image recognition based on local binary pattern. Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017), Chongqing, China.","DOI":"10.2991\/icmmcce-17.2017.199"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"52045","DOI":"10.1088\/1742-6596\/1187\/5\/052045","article-title":"An effective method for forest fire smoke detection","volume":"1187","author":"Qin","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7965","DOI":"10.1007\/s00521-020-05541-y","article-title":"Patchwise dictionary learning for video forest fire smoke detection in wavelet domain","volume":"33","author":"Wu","year":"2021","journal-title":"Neural Comput. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"89687","DOI":"10.1109\/ACCESS.2019.2926571","article-title":"Smoke-detection framework for high-definition video using fused spatial-and frequency-domain features","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1007\/s10694-019-00899-5","article-title":"Rapid early fire smoke detection system using slope fitting in video image histogram","volume":"56","author":"Wang","year":"2020","journal-title":"Fire Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"166947","DOI":"10.1016\/j.ijleo.2021.166947","article-title":"Video smoke detection with domain knowledge and transfer learning from deep convolutional neural networks","volume":"240","author":"Jia","year":"2021","journal-title":"Optik"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zheng, X., Chen, F., Lou, L., Cheng, P., and Huang, Y. (2022). Real-Time Detection of Full-Scale Forest Fire Smoke Based on Deep Convolution Neural Network. Remote Sens., 14.","DOI":"10.3390\/rs14030536"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1007\/s10694-019-00832-w","article-title":"Smoke detection on video sequences using 3D convolutional neural networks","volume":"55","author":"Lin","year":"2019","journal-title":"Fire Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1109\/TIP.2018.2876178","article-title":"Deep Video Dehazing With Semantic Segmentation","volume":"28","author":"Ren","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1007\/s11263-019-01235-8","article-title":"Single Image Dehazing via Multi-Scale Convolutional Neural Networks with Holistic Edges","volume":"128","author":"Ren","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1007\/s10694-019-00831-x","article-title":"Forest fire smoke detection based on visual smoke root and diffusion model","volume":"55","author":"Gao","year":"2019","journal-title":"Fire Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1007\/s10694-020-01052-3","article-title":"Full-scale video-based detection of smoke from forest fires combining ViBe and MSER algorithms","volume":"57","author":"Gao","year":"2021","journal-title":"Fire Technol."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lou, L., Chen, F., Cheng, P., and Huang, Y. (2022). Smoke root detection from video sequences based on multi-feature fusion. J. For. Res., 1\u201316.","DOI":"10.1007\/s11676-022-01461-w"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.rti.2004.12.004","article-title":"Real-time foreground-background segmentation using codebook model","volume":"11","author":"Kim","year":"2005","journal-title":"Real-Time Imaging"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1016\/j.patcog.2006.05.024","article-title":"A consensus-based method for tracking: Modelling background scenario and foreground appearance","volume":"40","author":"Wang","year":"2007","journal-title":"Pattern Recognit."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1109\/TIP.2010.2101613","article-title":"ViBe: A universal background subtraction algorithm for video sequences","volume":"20","author":"Barnich","year":"2010","journal-title":"IEEE Trans. Image Process."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1016\/j.patrec.2005.11.005","article-title":"Efficient adaptive density estimation per image pixel for the task of background subtraction","volume":"27","author":"Zivkovic","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","article-title":"Single image haze removal using dark channel prior","volume":"33","author":"He","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1145\/357994.358023","article-title":"A fast parallel algorithm for thinning digital patterns","volume":"27","author":"Zhang","year":"1984","journal-title":"Commun. ACM"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1002\/fam.2724","article-title":"A smoke segmentation algorithm based on improved intelligent seeded region growing","volume":"43","author":"Zhao","year":"2019","journal-title":"Fire Mater."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/18\/6748\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:24:43Z","timestamp":1760142283000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/18\/6748"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,7]]},"references-count":27,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["s22186748"],"URL":"https:\/\/doi.org\/10.3390\/s22186748","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,9,7]]}}}