Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 237-241.doi: 10.11896/JsJkx.191000196

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Candidate Region Detection Method for Maritime Ship Based on Visual Saliency

LIU Jun-qi1, LI Zhi2 and ZHANG Xue-yang2   

  1. 1 Graduate School,Space Engineering University,BeiJing 101416,China
    2 Space Engineering University,BeiJing 101416,China
  • Published:2020-07-07
  • About author:LIU Jun-qi, born in 1995, postgraduate.His main research interests include obJect detection and artificial intelligence.
    LI Zhi, born in 1973, Ph.D, professor, Ph.D supervisor.His main research interests include space system application and so on.

Abstract: Maritime ship detection technology has important civil and military value.Aiming at the problem of low accuracy of ship detection in complex sea scenes,a candidate region detection method for maritime ship based on visual saliency is proposed.In order to detect all the candidate regions of ships,the proposed method firstly uses Scharr edge detection operator to extract the edge contour features of salient targets,and then uses FT to obtain the final detection results of candidate regions based on the edge detection results.Experimental results on publicly available remote databases show that the proposed method gets good detection results in the detection of candidate regions of ships in a variety of complex marine scenes and realizes the quick extraction of the candidate regions of ships.

Key words: Candidate region extraction, FT saliency model, Remote sensing image, Scharr edge detection operator

CLC Number: 

  • TP391
[1] LECLERC M,THARMARASA R,FLOREA M C,et al.Ship Classification Using Deep Learning Techniques for Maritime Target Tracking//2018 21st International Conference on Information Fusion (FUSION).UK:IEEE,2018:737-744.
[2] QI S,MA J,LIN J,et al.Unsupervised ship detection based on saliency and S-HOG descriptor from optical satellite images.IEEE Geoscience and Remote Sensing Letters,2015,12(7):1451-1455.
[3] LEI R,CHAOJIAN S,XIN R.Salient target detection method under sea surface environment based on multi-scale phase spectrum//2011 Seventh International Conference on Natural Computation (ICNC).Shanghai,China:IEEE,2011,2:977-981.
[4] SONG Z,SUI H,WANG Y.Automatic ship detection for optical satellite images based on visual attention model and LBP//2014 IEEE Workshop on Electronics,Computer and Applications (IWECA).Ottawa,Canada:IEEE,2014.
[5] ACHANTA R,HEMAMI S,ESTRADA F,et al.Frequencytuned salient region detection//IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2009).2009 (CONF):1597-1604.
[6] NUR S A,IBRAHIM M M,ALI N M,et al.Vehicle detection based on underneath vehicle shadow using edge features//2016 6th IEEE International Conference on Control System,Computing and Engineering (ICCSCE).IEEE,2016:407-412.
[7] KANOPOULOS N,VASANTHAVADA N,BAKER R L.Design of an image edge detection filter using the Sobel operator .IEEE Journal of Solid-state Circuits,1988,23(2):358-367.
[8] JHNE B,SCHARR H,KRKEL S.Principles of filter design//Handbook of Computer Vision and Applications.Academic Press,1999.
[9] ACHANTA R,ESTRADA F,WILS P,et al.Salient region detection and segmentation//International Conference on Computer Vision Systems.Springer,2008:66-75.
[10] ITTI L,KOCH C,NIEBUR E.A model of saliency-based visual attention for rapid scene analysis.IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(11):1254-1259.
[11] CHENG M M,ZHANG G X,MITRA N J,et al.Global Contrast Based Salient Region Detection//2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).IEEE,2011.
[12] ZHAI Y,SHAH M.Visual attention detection in video sequences using spatiotemporal cues//Proceedings of the 14th ACM International Conference on Multimedia.Santa Barbara,CA,USA,ACM,2006:23-27.
[13] GUO C,MA Q,ZHANG L.Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform//2008 IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2008:1-8.
[14] HOU X,ZHANG L.Saliency detection:A spectral residual approach[C]//CVPR’07.IEEE,2007:1-8.
[15] HAREL J,KOCH C,PERONA P.Graph-based visual saliency//Advances in Neural Information Processing Systems.2007:545-552.
[16] ACHANTA R,SüSSTRUNK S.Saliency detection using maximum symmetric surround//2010 IEEE International Conference on Image Processing.IEEE,2010:2653-2656.
[17] MURRAY N,VANRELL M,OTAZU X,et al.Saliency estimation using a non-parametric low-level vision model//CVPR 2011.IEEE,2011:433-440.
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