Jeng-Horng Chang

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In this paper, we present a novel multi-modal histogram thresholding method in which no a priori knowledge about the number of clusters to be extracted is needed. The proposed method combines regularization and statistical approaches. By converting the approaching histogram thresholding problem to the mixture Gaussian density modeling problem, threshold(More)
Ridges and ravines are the main components constituting a "ngerprint. Traditional automatic "ngerprint identi"ca-tion systems (AFIS) are based on minutiae matching techniques. The minutiae for "ngerprint identi"cation are de"ned by ridge termination and ridge bifurcation. Most AFIS perform ridge line following process to automatically detect minutiae based(More)
In this paper, a novel filter-based greedy modular subspace (GMS) technique is proposed to improve the accuracy of high-dimensional data classification. The proposed approach initially divides the whole set of high-dimensional features into several arbitrary number of highly correlated subgroups by performing a greedy correlation matrix reordering(More)
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