Research Article Open Access

Automatic Target Recognition in Cluttered Visible Imagery

M. Jasmine Pemeena Priyadarsini1, K. Murugesan2, Srinivasa Rao Inbathini1, Y. Saiteja1 and Vemana Janith1
  • 1 VIT University, India
  • 2 , India

Abstract

Detection of a target from among similar/dissimilar targets in a cluttered image is vital in automatic target recognition. A MACH filter is used for the target detection in cluttered imagery. The cluttered images are correlated using the filter formulated from training images. The target is expected to be detected in the first highest peak. MACH was assumed as an optimum filter for target detection, but results proved that the accuracy is low. So, a new approach is identified for design of an optimum filter. The top ten peaks are identified as Regions of Interest (ROI’s) and these regions are correlated with all the training images using matched filter in the second stage. To further increase the accuracy, edge enhancement of the training set and input images using Sobel operator is done. Results proved that these new approaches greatly improved the accuracy. Using matched filter in the second stage after MACH gives us an advantage of identifying the orientation of the target as well.

Journal of Computer Science
Volume 9 No. 5, 2013, 572-582

DOI: https://doi.org/10.3844/jcssp.2013.572.582

Submitted On: 6 March 2012 Published On: 21 May 2013

How to Cite: Priyadarsini, M. J. P., Murugesan, K., Inbathini, S. R., Saiteja, Y. & Janith, V. (2013). Automatic Target Recognition in Cluttered Visible Imagery. Journal of Computer Science, 9(5), 572-582. https://doi.org/10.3844/jcssp.2013.572.582

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Keywords

  • MACH Filter
  • ROI
  • Sobel Operator