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One of the main issues is accurate moving object detection in real-time in a video with challenging background scenes. Numerous existing approaches used multiple features simultaneously to address the problem but did not consider any adaptive\/dynamic weight factor to combine these feature spaces. Being inspired by these observations, we propose a background subtraction-based real-time moving object detection method, called DFC-D. This proposal determines an adaptive\/dynamic weight factor to provide a weighted fusion of non-smoothing color\/gray intensity and non-smoothing gradient magnitude. Moreover, the color-gradient background difference and segmentation noise are employed to modify thresholds and background samples. Our proposed solution achieves the best trade-off between detection accuracy and algorithmic complexity on the benchmark datasets while comparing with the state-of-the-art approaches.<\/jats:p>","DOI":"10.1007\/s11042-022-12446-6","type":"journal-article","created":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T17:07:43Z","timestamp":1649869663000},"page":"32549-32580","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["DFC-D: A dynamic weight-based multiple features combination for real-time moving object detection"],"prefix":"10.1007","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6865-6650","authenticated-orcid":false,"given":"Md Alamgir","family":"Hossain","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1085-2461","authenticated-orcid":false,"given":"Md Imtiaz","family":"Hossain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6080-9720","authenticated-orcid":false,"given":"Md Delowar","family":"Hossain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0184-6975","authenticated-orcid":false,"given":"Eui-Nam","family":"Huh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,13]]},"reference":[{"key":"12446_CR1","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1016\/j.patcog.2017.09.040","volume":"76","author":"M Babaee","year":"2018","unstructured":"Babaee M, Dinh D T, Rigoll G (2018) A deep convolutional neural network for video sequence background subtraction. 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