{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:49:25Z","timestamp":1761648565539,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,4]],"date-time":"2018-08-04T00:00:00Z","timestamp":1533340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Contour is a very important feature in biological visual cognition and has been extensively investigated as a fundamental vision problem. In connection with the limitations of conventional models in detecting image contours in complex scenes, a hierarchical image contour extraction method is proposed based on the biological vision mechanism that draws on the perceptual characteristics of the early vision for features such as edges, shapes, and colours. By simulating the information processing mechanisms of the cells\u2019 receptive fields in the early stages of the biological visual system, we put forward a computational model that combines feedforward, lateral, and feedback neural connections to decode and obtain the image contours. Our model simulations and their results show that the established hierarchical contour detection model can adequately fit the characteristics of the biological experiment, quickly and effectively detect the salient contours in complex scenes, and better suppress the unwanted textures.<\/jats:p>","DOI":"10.3390\/s18082559","type":"journal-article","created":{"date-parts":[[2018,8,7]],"date-time":"2018-08-07T03:44:18Z","timestamp":1533613458000},"page":"2559","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Biologically Inspired Hierarchical Contour Detection with Surround Modulation and Neural Connection"],"prefix":"10.3390","volume":"18","author":[{"given":"Shuai","family":"Li","sequence":"first","affiliation":[{"name":"Aeronautical Engineering College, Air Force Engineering University, Xi\u2019an 710038, China"}]},{"given":"Yuelei","family":"Xu","sequence":"additional","affiliation":[{"name":"Aeronautical Engineering College, Air Force Engineering University, Xi\u2019an 710038, China"},{"name":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"given":"Wei","family":"Cong","sequence":"additional","affiliation":[{"name":"Aeronautical Engineering College, Air Force Engineering University, Xi\u2019an 710038, China"}]},{"given":"Shiping","family":"Ma","sequence":"additional","affiliation":[{"name":"Aeronautical Engineering College, Air Force Engineering University, Xi\u2019an 710038, China"}]},{"given":"Mingming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Aeronautical Engineering College, Air Force Engineering University, Xi\u2019an 710038, China"}]},{"given":"Min","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","article-title":"Contour Detection and Hierarchical Image Segmentation","volume":"33","author":"Arbelaez","year":"2011","journal-title":"IEEE Trans. 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