Paper Titles
The Software Design of Camellia Oleifera Seed Hyperspectral Detection System
p.1076
Nonlinear Regression Analysis for Programming and Engineering Application
p.1080
Research on Synchronous Parallel Coding Algorithm of Medium Length BCH and FPGA Implementation
p.1084
The Global Characteristic Cluster to the Base Station Classification
p.1088
Ship Detection Algorithm Based on Visual Cognition
p.1092
The Outdoor Data Collection System with GPRS
p.1098
Driving Posture Recognition by Joint Application of Motion History Image and Pyramid Histogram of Oriented Gradients
p.1102
Evaluation of Crowd Motion Direction Based on Wavelet Transform
p.1106
Pitch Detection Method Based on HHT
p.1111

Ship Detection Algorithm Based on Visual Cognition

Article Preview

Abstract:

In this paper, according to the phenomenon that the retina will strongly respond to large contrast visual stimulation and the generation mechanism of visual information in the primary visual cortex, we propose a method generating saliency map and detecting ship objects in satellite optical images. The method can detect significant contrast objects without considering the shape, edge or other forms of prior knowledge of the objects. In ship detection experiment, the results show the detection method based on visual contrast can effectively concentrate on the objects with greater contrast and achieve good detection results.

You might also be interested in these eBooks
Advances in Mechatronics, Automation and Applied Information Technologies View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1092-1097

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1092

Citation:

Cite this paper

Online since:

November 2013

Authors:

Xiao Guang Hu*, Cheng Qi Cheng, De Ren Li

Keywords:

Primary Visual Cortex, Saliency Map, Ship Detection, Visual Contrast

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] Crisp, D., The State-of-the-Art in Ship Detection in Synthetic Aperture Radar Imagery. (2004).

Google Scholar

[2] CORBANE, C., et al., A complete processing chain for ship detection using optical satellite imagery. International Journal of Remote Sensing, 2010. 31(22): pp.5837-5854.

DOI: 10.1080/01431161.2010.512310

Google Scholar

[3] Zhu, C. and H.W. Zhou, Run-sheng; Guo, Jun, A Novel Hierarchical Method of Ship Detection from Spaceborne Optical Image Based on Shape and Texture Features Geoscience and Remote Sensing, IEEE Transactions on, 2010. 48(9): pp.3446-3456.

DOI: 10.1109/tgrs.2010.2046330

Google Scholar

[4] Proia, N., Characterization of a Bayesian Ship Detection Method in Optical Satellite Images Geoscience and Remote Sensing Letters, IEEE, 2010. 7(2): pp.226-230.

DOI: 10.1109/lgrs.2009.2031826

Google Scholar

[5] Zhicheng, L., Q. Shiyin, and I. Laurent, Extraction of saliency-gist features and target detection for remote sensing images. (2010).

Google Scholar

[6] Fukun, B., et al., A Visual Search Inspired Computational Model for Ship Detection in Optical Satellite Images. Geoscience and Remote Sensing Letters, IEEE, 2012. 9(4): pp.749-753.

DOI: 10.1109/lgrs.2011.2180695

Google Scholar

[7] Feng, C., et al. Graph-based ship extraction scheme for optical satellite image. in Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International. (2011).

DOI: 10.1109/igarss.2011.6049172

Google Scholar

[8] Gaopan, H., et al. Ship Detection Using Texture Statistics from Optical Satellite Images. in Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on. (2011).

DOI: 10.1109/dicta.2011.91

Google Scholar

[9] Yang, G., Q. Lu, and F. Gao. A Novel Ship Detection Method Based on Sea State Analysis from Optical Imagery. in Image and Graphics (ICIG), 2011 Sixth International Conference on. (2011).

DOI: 10.1109/icig.2011.19

Google Scholar

[10] Wolfe, J.M. and T.S. Horowitz, What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 2004. 5(6): pp.495-501.

DOI: 10.1038/nrn1411

Google Scholar

[11] Riesenhuber, M. and T. Poggio, Hierarchical models of object recognition in cortex. Nature neuroscience, 1999. 2(11): pp.1019-1025.

DOI: 10.1038/14819

Google Scholar

[12] Mannan, S.K., C. Kennard, and M. Husain, The role of visual salience in directing eye movements in visual object agnosia. Current biology, 2009. 19(6): p. R247-R248.

DOI: 10.1016/j.cub.2009.02.020

Google Scholar

[13] Chen, T., et al. Sketch2Photo: internet image montage. in ACM Transactions on Graphics (TOG). 2009. ACM.

Google Scholar

[14] Rutishauser, U., et al. Is bottom-up attention useful for object recognition? in Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on. (2004).

DOI: 10.1109/cvpr.2004.1315142

Google Scholar

[15] Han, J., et al., Unsupervised extraction of visual attention objects in color images. Circuits and Systems for Video Technology, IEEE Transactions on, 2006. 16(1): pp.141-145.

DOI: 10.1109/tcsvt.2005.859028

Google Scholar

[16] Itti, L., C. Koch, and E. Niebur, A model of saliency-based visual attention for rapid scene analysis. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1998. 20(11): pp.1254-1259.

DOI: 10.1109/34.730558

Google Scholar

[17] Callaway, E.M., Neural mechanisms for the generation of visual complex cells. Neuron, 2001. 32(3): pp.378-380.

DOI: 10.1016/s0896-6273(01)00497-4

Google Scholar

[18] Sakai, K. and S. Tanaka, Spatial pooling in the second-order spatial structure of cortical complex cells. Vision Research, 2000. 40(7): pp.855-871.

DOI: 10.1016/s0042-6989(99)00230-8

Google Scholar

[19] Lampl, I., et al., Intracellular measurements of spatial integration and the MAX operation in complex cells of the cat primary visual cortex. Journal of neurophysiology, 2004. 92(5): pp.2704-2713.

DOI: 10.1152/jn.00060.2004

Google Scholar