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Review on line detection of wood panel images
- 1 Huzhou University
- 2 Huzhou University
- 3 Huzhou University
- 4 Huzhou University
* Author to whom correspondence should be addressed.
Abstract
In industrial, the modern intelligent degree of board counting is relatively low. Some small manufacturers still count by hand, but for large factories, manual counting needs a lot of human resources, and the accuracy of counting is low. With the rapid development of modern intelligence, image recognition is becoming more mature, some traditional algorithms keep emerging, such as Hough Transform, Fast Line Detector (FLD), Line Segment Detector (LSD) and other line detection algorithms, they have their own advantages and disadvantages, and are summarized and tested, compare which algorithm has higher accuracy and better effect in the field of board linear detection and counting. Finally, the operation mechanism, advantages and disadvantages are summarized, and the process and trend of the further optimization and development of the traditional algorithm line detection technology in the future are prospected, which provides some reference for the research in related fields.
Keywords
Straight line detection, Hough Transform, FLD, LSD
[1]. DAVIS A D,NOSEWORTHY M D. Motion and distortion correction of skeletal muscle echo planar images. Magnetic Resonance Imaging, 2016,21(7): 196-202.
[2]. HENG Hang jia, ZHONG Baojiang. Overview and evaluation of image straight line segment detection algorithms. Com-puter Engineering and Applications, 2019, 55(17) 9-19.
[3]. Micusik B,Wildenauer H.Descriptor free visual indoor localization with line segments//IEEE Conference on Computer Vision and Pattern Recognition,Boston,USA,2015: 3165-3173
[4]. Pumarola A,Vakhitov A,Agudo A,et al.PL- SLAM:real-time monocular visual SLAM with points and lines// IEEE Conference on Robotics and Automation,Singa-pore,2017: 4503-4508.
[5]. Zhou H,Zou D, Pei L, et al.Structslam: visual SLAM with building structure lines.IEEE Transactions on Vehicular Technology, 2015, 64(4): 1364-1375.
[6]. Bista S R,Giordano P R,Chaumette F.Appearance-based indoor navigation by IBVS using line segments. IEEE Robotics and Automation Letters, 2016, 1 (1) : 423-430.
[7]. Lian Lin, Li Guohui, Zhang Jun, et al. Automatic registration algorithm of infrared and visible images based on step-by-step parameter estimation. Acta electronica Sinica,2012,40(9): 1829-1838.
[8]. Xue N,Xia G S,Bai X,et al.Anisotropic-scale junction detection and matching for indoor images.IEEE Trans-actions on Image Processing,2018,27(1):78-91.
[9]. Wang L,Neumann U,You S.Wide-baseline image matching using line signatures//IEEE Conference on Computer Vision,Kyoto,Japan,2009:1311-1318
[10]. Kroeger T,Dai D,Gool L V.Joint vanishing point extraction and tracking//IEEE Conference on Computer Vision and Pattern Recognition,Boston,USA,2015:2449-2457
[11]. Lezama J,Grompone Von Gioi R,Randall G,et al.Finding vanishing points via point alignments in image primal and dual domains//IEEE Conference on Computer Vision and Pattern Recognition,Columbus,USA,2014:509-515
[12]. Yoo J H,Lee S W,Park S K,et al.A robust lane detection method based on vanishing point estimation using the relevance of line segments.IEEE Transactions on Intelligent Transportation Systems,2017,18(12):3254- 3266.
[13]. Ramalingam S,Brand M.Lifting 3d manhattan lines from a single image//IEEE International Conference on Computer Vision,Sydney,Australia,2013:497-504.
[14]. Sugiura T,Torii A,Okutomi M.3D surface reconstruction from point- and-line cloud//International Conference on 3D Vision,Lyon,France,2015:264-272.
[15]. Micusik B,Wildenauer H.Structure from motion with line segments under relaxed endpoint constraints.International Journal of Computer Vision,2016,124(1):65-79.
[16]. Miao qiguang, Weng Wenqi, Xu Pengfei. A new algorithm for water free bridge recognition in remote sensing images. Acta electronica Sinica,2011,39(7):1698-1701.
[17]. Tang Gefu,Xiao Zhifeng,Liu Qing,et al.A novel airport detection method via line segment classification and texture classification.IEEE Geoscience and Remote Sensing Letters,2015,12(12):2408-2412.
[18]. Budak U,Halici U,Sengur A,et al.Efficient airport detection using line segment detector and fisher vector representation[J].IEEE Geoscience and Remote Sensing Letters,2016,13(8):1079-1083.
[19]. Li Xuan, Liu Yunqing, Bian Chunjiang, et al. Detection of alongside ships in optical remote sensing images under local salient features. Chinese Journal of image and graphics,2016,21(5): 657-664.
[20]. Hofer M,Maurer M,Bischof H.Efficient 3d scene abstraction using line segments.Computer Vision and Image Understanding,2017,157:167-178.
[21]. Duda R O,Hart P E.Use of the hough transformation to detect lines and curves in pictures.Communications of the ACM,1972,15(1):11-15.
Cite this article
Meng,D.;Long,W.;Hu,L.;Jiang,L. (2024). Review on line detection of wood panel images. Advances in Engineering Innovation,5,24-32.
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