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patiant銅蟲(chóng) (著名寫(xiě)手)
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小蟲(chóng)在Optical Engineering 上發(fā)了一篇論文，急求檢索與否。若檢索了，還請(qǐng)大蟲(chóng)復(fù)制詳細(xì)的檢索信息啊，檢索number啊。 title: Expansion of the visual angle of a car rear-view image via an image mosaic algorithm source:Optical Engineering DOI: 10.1117/1.OE.54.5.053101 vol.54 no.(5) date: May 2015 若檢索了，請(qǐng)復(fù)制詳細(xì)檢索信息（或截圖也行）。小蟲(chóng)不甚感激��！ |
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Accession number: 20152000852396 Title: Expansion of the visual angle of a car rear-view image via an image mosaic algorithm Authors: Wu, Zhuangwen1 ; Zhu, Liangrong1 ; Sun, Xincheng1 Author affiliation: 1 Zhejiang Industry Polytechnic College, Automobile Department, 151 Qutun, Shaoxing, Zhejiang Province, China Corresponding author: Wu, Zhuangwen Source title: Optical Engineering Abbreviated source title: Opt Eng Volume: 54 Issue: 5 Issue date: May 1, 2015 Publication year: 2015 Article number: 150029 Language: English ISSN: 00913286 E-ISSN: 15602303 CODEN: OPEGAR Document type: Journal article (JA) Publisher: SPIE Abstract: The rear-view image system is one of the active safety devices in cars and is widely applied in all types of vehicles and traffic safety areas. However, studies made by both domestic and foreign researchers were based on a single image capture device while reversing, so a blind area still remained to drivers. Even if multiple cameras were used to expand the visual angle of the car's rear-view image in some studies, the blind area remained because different source images were not mosaicked together. To acquire an expanded visual angle of a car rear-view image, two charge-coupled device cameras with optical axes angled at 30 deg were mounted below the left and right fenders of a car in three light conditions-sunny outdoors, cloudy outdoors, and an underground garage-to capture rear-view heterologous images of the car. Then these rear-view heterologous images were rapidly registered through the scale invariant feature transform algorithm. Combined with the random sample consensus algorithm, the two heterologous images were finally mosaicked using the linear weighted gradated in-and-out fusion algorithm, and a seamless and visual-angle-expanded rear-view image was acquired. The four-index test results showed that the algorithms can mosaic rear-view images well in the underground garage condition, where the average rate of correct matching was the lowest among the three conditions. The rear-view image mosaic algorithm presented had the best information preservation, the shortest computation time and the most complete preservation of the image detail features compared to the mean value method (MVM) and segmental fusion method (SFM), and it was also able to perform better in real time and provided more comprehensive image details than MVM and SFM. In addition, it had the most complete image preservation from source images among the three algorithms. The method introduced by this paper provided the basis for researching the expansion of the visual angle of a car rear-view image in all-weather conditions. © 2015 Society of Photo-Optical Instrumentation Engineers. Number of references: 31 Main heading: Image matching Controlled terms: Algorithms - Cameras - CCD cameras - Charge coupled devices - Garages (parking) - Image fusion Uncontrolled terms: heterologous images - Image mosaic - mosaic evaluation - rear-view image - Visual angle Classification code: 402.2 Public Buildings - 714.2 Semiconductor Devices and Integrated Circuits - 723 Computer Software, Data Handling and Applications - 723.2 Data Processing and Image Processing - 742.2 Photographic Equipment - 921 Mathematics DOI: 10.1117/1.OE.54.5.053101 Database: Compendex Compilation and indexing terms, © 2015 Elsevier Inc. Copyright © 2015 Elsevier B.V. All rights reserved. Cookies are set by this site. To decline them or learn more, visit our Cookies page. |
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