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Residual analysis for feature detection

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3 Author(s)
M. -H. Chen ; Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY, USA ; D. Lee ; T. Pavlidis

It is shown that in a very simple form residual analysis achieves results that are at least as good as if not better than those obtained by other techniques. There are many ways for extensions of the method. For example, moving average filters of regularization can be used to obtain the residual images. Also, the strength of the correlation, measured by Drr(O), can be used to eliminate noise, weak edges, etc. A more ambitious extension is by considering smoothing filters that leave invariant the function representing the reflectance from smooth surfaces

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IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:13 ,  Issue: 1 )