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Step-by-step pipeline processing approach for line segment detection
Shao CY(邵春艳); Ding QH(丁庆海); Luo HB(罗海波); Chang Z(常铮); Zhang, Chi; Zheng, Tianjiang
Department光电信息技术研究室
Source PublicationIET Image Processing
ISSN1751-9659
2017
Volume11Issue:6Pages:416-424
Indexed BySCI ; EI
EI Accession number20172503793568
WOS IDWOS:000403406800009
Contribution Rank2
Funding OrganizationNational Science and Technology Support Project [2014BAF10B00] ; Major science and technology special fund for projects of Zhejiang Province [2015C01SA750002] ; Natural Science Foundation of Ningbo [2015A610144] ; Ningbo international cooperation project [2015D10010]
KeywordImage Segmentation Affine Transforms Edge Detection Eigenvalues And Eigenfunctions Line Segment Detection Step-by-step Pipeline Processing Approach Resistant To Affine Transformation And monoTonic Intensity Change descripTor Ratmic Descriptor Canny Detector Harris Corner Detector Regions Of Interest
AbstractThis study proposes a line segment detection that can efficiently and effectively handle non-linear uniform intensity changes. The presented sketching algorithm applies the resistant to affine transformation and monotonic intensity change (RATMIC) descriptor to conduct binary translation in the image pre-processing step, which can remove the unwanted smoothing of the Canny detector in most line detections. The Harris corner detector is applied to catch regions of line segments for the purpose of simulating the composition of sketching and achieving a sense of unity within the picture. Furthermore, the RATMIC descriptor is employed to obtain binary images of the regions of interest (ROIs). Finally, small eigenvalue analysis is implemented to detect straight lines in the ROIs. The experiments conducted on various images with image rotation, scaling, and translation validate the effectiveness of the proposed method. The experimental results also demonstrate that about 30% in the overall coverage of major lines and 20% in the coverage per major line are increased compared with the state-of-the-art line detectors. Moreover, the performance of the proposed method produces a combined advantage of ~17% in the coverage of line segments over the line segment detector with noisy images.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology
WOS KeywordTECTONIC LINEAMENT ANALYSIS ; MATLAB-BASED TOOLBOX ; HOUGH TRANSFORM ; CORNER DETECTION ; SATELLITE IMAGES ; EXTRACTION ; ALGORITHM ; TECLINES ; DEMS
WOS Research AreaComputer Science ; Engineering ; Imaging Science & Photographic Technology
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20751
Collection光电信息技术研究室
Corresponding AuthorShao CY(邵春艳)
Affiliation1.Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology of Zhejiang Province, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Key Laboratory of Opt-Electronic Information Processing, Chinese Academy of Sciences, Shenyang 110016, China
4.Space Star Technology Co., Ltd., Beijing, 100086, China
Recommended Citation
GB/T 7714
Shao CY,Ding QH,Luo HB,et al. Step-by-step pipeline processing approach for line segment detection[J]. IET Image Processing,2017,11(6):416-424.
APA Shao CY,Ding QH,Luo HB,Chang Z,Zhang, Chi,&Zheng, Tianjiang.(2017).Step-by-step pipeline processing approach for line segment detection.IET Image Processing,11(6),416-424.
MLA Shao CY,et al."Step-by-step pipeline processing approach for line segment detection".IET Image Processing 11.6(2017):416-424.
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