KEYWORDS: Performance modeling, Optical character recognition, Data modeling, Detection and tracking algorithms, Quantization, Curium, Systems modeling, Statistical modeling, Data storage, Optimization (mathematics)
The language model design and implementation issue is researched in this paper. Different from previous research,
we want to emphasize the importance of n-gram models based on words in the study of language model. We build up a
word based language model using the toolkit of SRILM and implement it for contextual language processing on Chinese
documents. A modified Absolute Discount smoothing algorithm is proposed to reduce the perplexity of the language
model. The word based language model improves the performance of post-processing of online handwritten character
recognition system compared with the character based language model, but it also increases computation and storage
cost greatly. Besides quantizing the model data non-uniformly, we design a new tree storage structure to compress the
model size, which leads to an increase in searching efficiency as well. We illustrate the set of approaches on a test corpus
of recognition results of online handwritten Chinese characters, and propose a modified confidence measure for
recognition candidate characters to get their accurate posterior probabilities while reducing the complexity. The weighted
combination of linguistic knowledge and candidate confidence information proves successful in this paper and can be
further developed to achieve improvements in recognition accuracy.
A new sequence matching based feature extracting method is proposed in this paper, and the method is applied to on-line signature verification. The signature is first extracted as a point sequence in writing order. Then the sequence is matched with a model sequence that is extracted from the model signature, utilizing a modified DTW matching criterion. Based on the matching result, the sequence is divided into a fixed number of segments. Local shape features are extracted from each segment, making use of the direction and length information. Experiments show that this new feature extracting method is more discriminative than other commonly used feature extracting method. When applied to an on-line signature verification system, current feature extracting method shows benefit in verifying users with large variations in their genuine signatures.
In this paper, a direction sequence string matching based on-line signature verification system is proposed. A signature is coded as a direction sequence string. The modified edit distance is used for string matching. The test signature is compared with 5 reference signatures and distance is given by averaging the 5 distances. A verification result is given by comparing the distance measure with a pre-calculated threshold. The experiment shows a result of 4.7% equal error rate (EER).
A frequency shift interferometer for absolute distance measurement using LD-pumped Nd:YVO4, microchip laser is proposed in this paper. The LD pumped Nd:YVO4 crystal microchip laser here is an external cavity laser. By modulating the voltage supplied to PZT, the frequency of the laser beam is modulated. A frequency shift interferometer using the technique of frequency-modulated continuous-wave is established. In this experiment setup a reference interferometer is used to compensate for the drift of the central frequency of the laser. The experimental results show that drift of central frequency of the laser affects the accuracy of the measurement a lot and can be compensated effectively. But influence from the drift of frequency modulation ratio tot eh accuracy can not be compensated.
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