Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Combined imaging matching method of side scan sonar images with prior position knowledge

Side scan sonar (SSS) image matching plays an important role in underwater applications, such as combining images to form wide range relief images, underwater simultaneous location and mapping, and construction of images of underwater terrain and objects. Because there are differences between the imaging mechanisms of SSS images and optical images, current matching algorithms for optical images do not always work well for SSS images. This study proposes a combined image matching approach for SSS images. First, the images are preprocessed to remove some environmental effects. Second, feature points that are stable for affine transformations are extracted from the SSS matching images based on speeded-up robust features with prior position knowledge. Third, geometric correction is made by the random sample consensus. After that, a similarity calculation is performed. The proposed approach speeds up the matching process and improves its accuracy by combining feature points matching and similarity calculation. It reduces the mismatching rate and the computation requirement by estimating the location uncertainty with prior knowledge and reducing the searching regions for image matching. Experiments show that the matching algorithm takes less time and has greater reliability and accuracy than traditional algorithms.

References

    1. 1)
      • 15. Gaidhane, V.H., Hote, Y.V., Singh, V.: ‘A computationally efficient approach for template matching-based image registration’, Sadhana, 2014, 39, (2), pp. 317331.
    2. 2)
      • 3. Kim, K., Neretti, N., Intrator, N.: ‘Mosaicing of acoustic camera images’, IEE Proc., Radar Sonar Navig., 2005, 152, pp. 263270.
    3. 3)
      • 13. Stalder, S., Bleuler, H., Ura, T.: ‘Terrain-based navigation for underwater vehicles using side scan sonar images’. OCEANS 2008, 2008, pp. 13.
    4. 4)
      • 19. Reed, S., Ruiz, I.T., Capus, C., et al: ‘The fusion of large scale classified side-scan sonar image mosaics’, IEEE Trans. Image Process., 2006, 15, (7), pp. 20492060.
    5. 5)
      • 10. Aulinas, J., Fazlollahi, A., Salvi, J., et al: ‘Robust automatic landmark detection for underwater SLAM using side-scan sonar imaging’. 11th Int. Conf. Mobile Robots and Competitions, 2011, pp. 2126.
    6. 6)
      • 22. Yang, M., Shen, C.: ‘A random sampling algorithm for fundamental matrix robust estimation’, J. Appl. Sci., 2004, 2, pp.12.
    7. 7)
      • 1. Chen, E., Huang, W., Wang, W.H., et al: ‘Side scan sonar grid Map for unmanned underwater vehicle navigation’. OCEANS 2011, Waikoloa, HI, 2011, pp. 18.
    8. 8)
      • 14. Lai, Y.: ‘Rotation moment invariant feature extraction techniques for image matching’, Appl. Mech. Mater., 2014, 721, pp. 775778.
    9. 9)
      • 17. Zhao, J., Wang, A., Zhang, H., et al: ‘Mosaic method of side-scan sonar strip images using corresponding features’, IET Image Process., 2013, 7, (6), pp. 616623.
    10. 10)
      • 11. Bay, H., Ess, A., Tuytelaars, T., et al: ‘Speeded-up robust features (SURF)’, Comput. Vis. Image Underst., 2008, 110, (3), pp. 346359.
    11. 11)
      • 16. Zhang, H., Zhao, J., Yang, K., et al: ‘Seabed topographic contour match based on angle code technique’. OCEANS 2010, Sydney, May 2010, pp. 14.
    12. 12)
      • 8. Ruiz, I.T., de Raucourt, S., Petillot, Y., et al: ‘Concurrent mapping and localization using sidescan sonar’, IEEE J. Ocean. Eng., 2004, 29, (2), pp. 442456.
    13. 13)
      • 7. Paull, L., Saeedi, S., Seto, M., et al: ‘AUV navigation and localization: a review’, IEEE J. Ocean. Eng., 2014, 39, pp. 131149.
    14. 14)
      • 2. Chavez, P.S., Isbrecht, J., Galanis, P., et al: ‘Processing, mosaicking and management of the Monterey Bay digital sidescan-sonar images’, Marine Geol., 2002, 181, (1-3), pp. 305315.
    15. 15)
      • 18. Hao, Y., Han, Q.: ‘Data fusion of multi-beam sonar and side-scan sonar base on feature contour registration’. 2011 Int. Conf. Consumer Electronics, Communications and Networks, April 2011, pp. 174177.
    16. 16)
      • 9. Fallon, M.F., Kaess, M., Johannsson, H., et al: ‘Efficient AUV navigation fusing acoustic ranging and side-scan sonar’. 2011 IEEE Int. Conf. Robotics and Automation (ICRA), May 2011, pp. 23982405.
    17. 17)
      • 6. Bikonis, K., Moszynski, M., Lubniewski, Z.: ‘Application of shape from shading technique for side scan sonar images’, Pol. Marit. Res., 2013, 20, (3), pp. 3944.
    18. 18)
      • 4. Dura, E., Bell, J., Lane, D.: ‘Reconstruction of textured seafloors from side-scan sonar images’, IEE Proc., Radar Sonar Navig., 2004, 151, (2), pp. 114126.
    19. 19)
      • 20. Tao, W., Liu, Y.: ‘Edge preserving filter of side scan sonar images with wavelet modulus maxima shift-correlative technique’, Int. J. Imaging Syst. Technol., 2011, 21, pp. 349355.
    20. 20)
      • 12. Vandrish, P., Vardy, A., Walker, D., et al: ‘Side scan sonar image registration for AUV navigation’. Int. Submarine Engineering, 2011, pp. 1017.
    21. 21)
      • 5. Coiras, E., Petillot, Y., Lane, D.M.: ‘Multiresolution 3-D reconstruction from side-Scan sonar images’, IEEE Trans. Image Process., 2007, 16, pp. 382390.
    22. 22)
      • 21. Lowe, D.G.: ‘Distinctive image features from scale-invariant keypoints’, Int. J. Comput. Vis., 2004, 60, (2), pp. 91110.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2017.0172
Loading

Related content

content/journals/10.1049/iet-ipr.2017.0172
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address