Abstract
Recognition of very low resolution patterns which cover only a few pixels in the image screen can not be made by the conventional recognition methods.
A theoretically new statistical pattern recognition method has been developed by the same author [1] for the recognition of patterns which are smaller than the size of the elementary pixel windows in the image. In this measurement the gray-level histogram of the objects examined is compared with the (calculated) gray-level densities of different possible objects, and the recognition is taken on the basis of the comparison. The examined pattern should be randomly distributed on the screen, or a random movement of camera (or target) is needed.
Now, effects of noise are analyzed and demonstrated through simulation and experiments, and noise models and noise reduction are suggested in the histogram domain.
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References
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© 1993 Springer-Verlag Berlin Heidelberg
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Szirányi, T. (1993). Noise effects in statistical subpixel pattern recognition. In: Chetverikov, D., Kropatsch, W.G. (eds) Computer Analysis of Images and Patterns. CAIP 1993. Lecture Notes in Computer Science, vol 719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57233-3_9
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DOI: https://doi.org/10.1007/3-540-57233-3_9
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