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In order to increase the road detection accuracy, a proposed method for road detection by GAC model with edge feature extraction and segmentation is studied in this paper. First, edge feature can be extracted using the proposed gradient magnitude with Canny operator. Then, a reconstructed gradient map is applied in watershed transformation method, which is segmented for the next initial contour. Last, with the combination of edge feature and initial contour, the boundary stopping function is applied in the GAC model. The road boundary result can be accomplished finally. Experimental results show, by comparing with other methods in [Formula: see text]-measure system, that the proposed method can achieve satisfying results. <\/jats:p>","DOI":"10.1142\/s021800142154032x","type":"journal-article","created":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T16:48:14Z","timestamp":1634230094000},"source":"Crossref","is-referenced-by-count":3,"title":["Road Detection Based on Edge Feature with GAC Model in Aerial Image"],"prefix":"10.1142","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7878-881X","authenticated-orcid":false,"given":"Linying","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Electronics and Control Engineering, Chang\u2018an University, Xi\u2018an, P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhou","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Chang\u2018an University, Xi\u2018an, P. R. 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