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필기체 한글의 오프라인 인식을 위한 효과적인 두 단계 패턴 정합 방법
박정선,이성환 대한전자공학회 1994 전자공학회논문지-B Vol.b31 No.4
In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.
KL 변환을 이용한 multilayer perceptron에 의한 한국어 연속 숫자음 인식
박정선,권장우,권정상,이응혁,홍승홍 대한전자공학회 1996 전자공학회논문지-B Vol.b33 No.8
In this paper, a new korean digita speech recognition technique was proposed using muktolayer perceptron (MLP). In spite of its weakness in dynamic signal recognition, MLP was adapted for this model, cecause korean syllable could give static features. It is so simle in its structure and fast in its computing that MLP was used to the suggested system. MLP's input vectors was transformed using karhunen-loeve transformation (KLT), which compress signal successfully without losin gits separateness, but its physical properties is changed. Because the suggested technique could extract static features while it is not affected from the changes of syllable lengths, it is effectively useful for korean numeric recognition system. Without decreasing classification rates, we can save the time and memory size for computation using KLT. The proposed feature extraction technique extracts same size of features form the tow same parts, front and end of a syllable. This technique makes frames, where features are extracted, using unique size of windows. It could be applied for continuous speech recognition that was not easy for the normal neural network recognition system.
RFID/USN기반 물류/유통 시스템의 평가를 위한 BSC 프레임워크
박정선 대한안전경영과학회 2014 대한안전경영과학회지 Vol.16 No.4
Many systems using RFID/USN were and are being developed. Some systems are used in practice and some are not. Generally, the main reasons not being used are: The prices of chips are too high considering the effects. The application domain is not appropriate for RFID/USN. So, various skills for higher sensing precision have been introduced like using multiple sensors and avoiding metals which deter sensings seriously. Now, it is time to evaluate systems which were developed using RFID/USN technology. However, no systematic approach has been made for the evaluation. In this paper, a framework using BSC is introduced for the evaluation of systems using RFID/USN. In this framework, some Critical Success Factors(CSF) are derived and some Key Performance Indices(KPI) are developed for each CSF.