• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.683-690
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• 2009

One of the major problems that prevent us from building a good recognition system for large-scale on-line Chinese character recognition using HMMs is increasing recognition time. In this paper, we propose a clustering method to solve recognition speed problem and an efficient distance measure between HMMs. From the experiments, we got about twice the recognition speed and 95.37% 10-candidate recognition accuracy, which is only 0.9% decrease, for 20,902 Chinese characters defined in Unicode CJK unified ideographs.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.207-213
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• 2011

In this paper, we present a study on the real-time implementation of mobile robot to which the interactive voice recognition technique is applied. The speech command utters the sentential connected word and asserted through the wireless remote control system. We implement an automatic distance speech command recognition system for voice-enabled services interactively. We construct a baseline automatic speech command recognition system, where acoustic models are trained from speech utterances spoken by a microphone. In order to improve the performance of the baseline automatic speech recognition system, the acoustic models are adapted to adjust the spectral characteristics of speech according to different microphones and the environmental mismatches between cross talking and distance speech. We illustrate the performance of the developed speech recognition system by experiments. As a result, it is illustrated that the average rates of proposed speech recognition system shows about 95% above.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.165-170
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• 2002

This study was carried out to measure the 3D-distance of a cow model teat for an application possibility on Robotic Milking System(RMS). A teat recognition algorithm was made to find 3D-distance of the model by using Gonzalrez's theory. Some of the results are as follows. 1 . In the distance measurement experiment on the test board, as the measured length, and the length between the center of image surface and the measured image point became longer, their error values increased. 2. The model teat was installed and measured the error value at the random position. The error value of X and Y coordinates was less than 5㎜, and that of Z coordinates was less than 20㎜. The error value increased as the distance of camera's increased. 3. The equation for distance information acquirement was satisfied with obtaining accurate distance that was necessary for a milking robot to trace teats, A teat recognition algorithm was recognized well four model cow teats. It's processing time was about 1 second. It appeared that a teat recognition algorithm could be used to determine the 3D-distance of the cow teat to develop a RMS.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.165-170
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• 2015

The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. The vector values of the existing system to the model created by configuring the database was used in the recognition vocabulary. The model to be formed during the search for the recognition vocabulary is recognizable because there is a disadvantage not configured with a database. In this paper, it induced to recognize the vector model is formed by the search and configuration using a Bayesian model recognizes the Bhattacharyya distance measurement based on the vector model, by applying the Wiener filter improves the recognition rate. The result of Convergence of two method's are improved reliability experiments for distance measurement. Using a proposed measurement are compared to the conventional method exhibited a performance of 98.2%.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.701-709
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• 2010

This paper presents an efficient signature recognition method by using the hybrid similarity criterion, which is in inverse proportion to distance and in proportion to correlation between the images. The distance is applied to express the spacial property of image, and the correlation is also applied to express the statistical property. The proposed criterion provides the robust recognition to both the geometrical variations such as position, size, and rotation and the shape variation. The normalized cross-correlation(NCC), which is calculated by considering 4 directions based on the histogram of binary image, is applied to express rapidly and accurately the similarity between the images. The proposed method has been applied to the problem for recognizing the 20 truck images of 288*288 pixels and the 105(3 persons * 35 images) signature images of 256*256 pixels, respectively. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well. Especially, the hybrid criterion of NCC and ordinal distance has a superior recognition performance to the hybrid criterion using city-block or Euclidean distance.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.367-372
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• 2013

In general, Levenshtein distance algorithm have a problem with not distinguish the consideration of vacabulary retrieve, because Levenshtein methode is used to vocabulary order are not defined. In this paper, we propose a improved Levenshtein methode, it effectively manage the vocabulary retrieve by frequency use of a vocabulary, and it gives the weight number which have a order between vocabularies. Therefore proposed methode have a advantage of solve the defect of perception rate in the case of increase the vocabulary, improve the recognition time become higher and it can be effectively retrieval space management.. System performance as a result of represent vocabulary dependence recognition rate of 97.81%, vocabulary independence recognition rate of 96.91% in indoor environment. Also, vocabulary dependence recognition rate of 91.11%, vocabulary independence recognition rate of 90.01% in outdoor environment.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.119-122
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• 2005

In this paper, we investigated the recognition range according to modulation index for the ISO(International Standards Organization) 14443 13.56MHz contactless Type B RFID(Radio Frequency IDentification) system. We measured recognition range with changing modulation index step by step from 5% to 24% where we used 4 samples of Type B transponder with different resonance frequencies between 13.838MHz and 17.200MHz. While gradually increasing a distance in vertical direction from the center of the reader antenna, we measured the distance where the transponder's PUPI(Pseudo Unique PICC(Proximity IC Card) Identifier) is recognized continuously during 10 seconds and the distance where the transponder's PUPI is recognized at least two times during 5 seconds. From the measurement results, we found that the best recognition ranges were achieved when the reader had modulation index between 11% and 14%.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.428-435
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• 2011

Many isolated word recognition systems may generate irrelevant words for recognition results because they use only acoustic information or small amount of language information. In this paper, I propose word similarity that is used for selecting (or removing) less common words from candidates by applying Levenshtein distance. Word similarity is obtained by using positional accuracy that reflects the frequency information along to character's alignment information. This paper also discusses various improving techniques of selection of disparate words. The methods include different loss values, phone accuracy based on confusion information, weights of candidates by ranking order and partial comparisons. Through experiments, I found that the proposed methods are effective for removing heterogeneous words without loss of performance.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.871-874
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• 1997

A new typed distance relaying scheme is proposed. Artificial neural networks are applied to the distance relaying system composed of pattern recognition based. The proposed distance relaying scheme have the two block of pattern recognition stages to estimate the fundamental frequency and to classify the fault types. The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.554-559
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• 2003

In this paper the possibility of snorer-dependent snore recognition using cepstral coefficients was suggested. We assumed that snore and speech sounds have some similarities and we used cepstral coefficients which are widely used for speech recognition. Snoring data were acquired from 18 persons including 5 patients diagnosed as snore patient. To evaluate the performance of proposed method, the distance ratio based on LPC cepstral coefficients was selected as an index for snorer-dependent snore recognition. As a result, distance ratio of 3 was selected as optimal value showing the most efficient snorer-dependent snore recognition, which is high accuracy of 95.05％ on average. In conclusion, the proposed method showed the possibilities to be applied in clinical applications for snorer-dependent snore recognition.