The Naval Weapons Cener (NWC)is currently developing automatic target clasification systems for future surveillance and atack aircraft and missile seekers. Target classification has been identified as a critical operational capability which should be included on new Navy aircraft and missile developments or systems undergoing significant modifications. In contrast to the radar data, the size of TV or IIR images of ships changes as a function of range. It is therefore necessary to develop feature extraction algorithms which are scale invariant. The central moments, which have scale and rotational invariant properties were therefore implemented. This method was suggested in 1962 by M.K. Hu (IRE Transactions on Information Theory). Using the moments alone resulted in unsatisfactory classification performance and indicated that edge enhancement was necessary and that the background needed to be rejected. The images were therefore processed with the Sobel nonlinear edge enhancement algorithm, which also has the desirable property that it works for images with low signal-to-noise ratios and poorly defined edges. Satisfactory results were obtained. In another experiment, the feature vector was composed of the five lower-order invariant moments and the five lower-order FFT coefficient squared magnitudes, excluding the zero frequency coefficient.


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    Title :

    Automatic classification of infrared ship imagery


    Additional title:

    Automatische Klassifizeirung der Infrarotaufnahmen von Schiffen


    Contributors:
    Kovar, J.J. (author) / Knecht, J. (author) / Chenoweth, D. (author)


    Publication date :

    1981


    Size :

    7 Seiten, 1 Bild, 5 Tabellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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