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Video artificial text detection is a challenging problem of pattern recognition. Current methods which are usually based on edge, texture, connected domain, feature or learning are always limited by size, location, language of artificial text in video. To solve the problems mentioned above, this paper applied SOM (Self-Organizing Map) based on supervised learning to video artificial text detection...
A pedestrian detection method by using kernel principle component analysis (KPCA) and Fisher linear discriminant (FLD) is presented in this paper. The basic idea of this method is to first utilize the KPCA algorithm to perform feature extraction, which obtains the nonlinear principle components in the high dimension feature space composed of haar wavelet coefficients, and then implement classification...
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