{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:38:43Z","timestamp":1760150323307,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T00:00:00Z","timestamp":1699315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52075354","72201186","BK20220481","22KJB410002","2023M731450"],"award-info":[{"award-number":["52075354","72201186","BK20220481","22KJB410002","2023M731450"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["52075354","72201186","BK20220481","22KJB410002","2023M731450"],"award-info":[{"award-number":["52075354","72201186","BK20220481","22KJB410002","2023M731450"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["52075354","72201186","BK20220481","22KJB410002","2023M731450"],"award-info":[{"award-number":["52075354","72201186","BK20220481","22KJB410002","2023M731450"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["52075354","72201186","BK20220481","22KJB410002","2023M731450"],"award-info":[{"award-number":["52075354","72201186","BK20220481","22KJB410002","2023M731450"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Single-circle detection is vital in industrial automation, intelligent navigation, and structural health monitoring. In these fields, the circle is usually present in images with complex textures, multiple contours, and mass noise. However, commonly used circle-detection methods, including random sample consensus, random Hough transform, and the least squares method, lead to low detection accuracy, low efficiency, and poor stability in circle detection. To improve the accuracy, efficiency, and stability of circle detection, this paper proposes a single-circle detection algorithm by combining Canny edge detection, a clustering algorithm, and the improved least squares method. To verify the superiority of the algorithm, the performance of the algorithm is compared using the self-captured image samples and the GH dataset. The proposed algorithm detects the circle with an average error of two pixels and has a higher detection accuracy, efficiency, and stability than random sample consensus and random Hough transform.<\/jats:p>","DOI":"10.3390\/s23229030","type":"journal-article","created":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T11:25:31Z","timestamp":1699356331000},"page":"9030","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Novel Four-Step Algorithm for Detecting a Single Circle in Complex Images"],"prefix":"10.3390","volume":"23","author":[{"given":"Jianan","family":"Cao","sequence":"first","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, China"}]},{"given":"Yue","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, China"}]},{"given":"Chuanyang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1007\/s13239-019-00421-6","article-title":"Automatic Segmentation, Detection, and Diagnosis of Abdominal Aortic Aneurysm (AAA) Using Convolutional Neural Networks and Hough Circles Algorithm","volume":"10","author":"Mohammadi","year":"2019","journal-title":"Cardiovasc. 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