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Historical Chinese character recognition has been a challenging topic in pattern recognition field because of large character set, various writing styles and lack of training samples. In this paper, we adopted Style Transfer Mapping (STM) method to historical Chinese character recognition. Optimal selection of parameters was discussed. Two sets of experiments were conducted. The first set of experiment...
The purpose of writing this paper is three-fold. First, it presents a novel local / part-based automatic system for forensic signature verification involving disguised signatures. Disguised signatures are written by authentic authors but with the intention of later denial. The proposed system reaches an equal error rate of 3.36% in classifying disguised and genuine signatures. Second, it compares...
In this paper, we present an innovative approach to integrate spatial relations in stroke clustering for handwritten Devanagari character recognition. It handles strokes of any number and order, writer independently. Learnt strokes are hierarchically agglomerated via Dynamic Time Warping based on their location and their number and stored accordingly. We experimentally validate our concept by showing...
The spatial relationships between two objects can be characterized by their interval relationship. The difference in spatial relationships can be determined by using an interval neighborhood graph. In this paper, we propose to adapt the weights in an interval neighborhood graph according to the significance of change in spatial relationships. We apply our proposed approach in the application of Chinese...
In this paper, we present a large scale offline handwritten Chinese character database-HCL2000 which will be made public available for the research community. The database contains 3,755 frequently used simplified Chinese-characters written by 1,000 different subjects. The writerspsila information is incorporated in the database to facilitate testing on grouping writers with different background such...
A new hidden Markov model (HMM) is proposed for on-line character recognition using two typical features, pen-direction feature and pen-coordinate feature. These two features are quite different in their stationarity; pen-direction feature is stationary within every line segment of a stroke whereas pen-coordinate feature is not. In the proposed HMM, these contrasting features are used in a separative...
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