Signature Verification using Integrated Classifiers
نویسنده
چکیده
This paper presents a new approach for off-line signature verification. The proposed system is based on global, grid, ink distribution and texture features. The Boosting algorithm is applied to train and integrate multiple classifiers, and the distance-based classifier used as the base classifier corresponding to each feature set. Adaptive threshold is associated with individuality. Experimental results show the system is insensitive to the order of base-classifiers and gets a high verification ratio.
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