• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.55-62
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• 2017

Non-negative matrix factorization (NMF) is one of the typical parts-based representation in which images are expressed as a linear combination of basis vectors that show the lcoal features or objects in the images. In this paper, we represent face images using various NMF methods and recognize their face identities based on extracted features using a learning vector quantization. We analyzed the various NMF methods by comparing extracted basis vectors. Also we confirmed the availability of NMF to the face recognition by verification of recognition rate of the various NMF methods.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.511-515
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• 1999

The main factor decreasing speech recognition rate is the surrounding noise. To lower the noise effect, we generally used the filter bank at preprocessing stage. But, in this paper, we tried to recognize the 10 numeral numbers using 2-D LPC to extract image feature. At first, we obtained the result of speech-only recognition using 13th-order LPC coefficients and then, for distorted speech recognition results of ‘0’, ‘4’, ‘5’, ‘6’ and 9’, we added image parameters such as 12th-order 2-D LPC coefficients. At each frame, we extracted the 2-D LPC coefficients, and simulated recognizer with two parameters such as speech and image. Finally, for the numbers, such as ‘4’and ‘9’, the better results were obtained.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.492-495
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• 1999

In this paper, a research is focused on implementation of the handwritten Korean-character recognition system using a neural coprocessor for PDA application. The proposed coprocessor is composed of a digital neural network called DMNN and a RISC-based dedicated controller in order to achieve high speed as well as compactness. Two neural networks are used for recognition, one for stroke classification out of extended 11 strokes and the other for grapheme classification. Our experimental result shows that the successful recognition rate of 92.1% over 3,000 characters written by 10 persons can be obtained. Moreover, it can be improved to 95.3% when four candidates are considered. The design verification of tile proposed neural coprocessor is conducted using the ASIC emulator for further hardware implementation.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1383-1392
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• 2014

In this paper, we proposed a method to automatically determine the optimal radius through multi-scale LBP operation generalizing the size of radius variation and boosting learning in facial emotion recognition. When we looked at the distribution of features vectors, the most common was $LBP_{8.1}$ of 31% and sum of $LBP_{8.1}$ and $LBP_{8.2}$ was 57.5%, $LBP_{8.3}$, $LBP_{8.4}$, and $LBP_{8.5}$ were respectively 18.5%, 12.0%, and 12.0%. It was found that the patterns of relatively greater radius express characteristics of face well. In case of normal and anger, $LBP_{8.1}$ and $LBP_{8.2}$ were mainly distributed. The distribution of $LBP_{8.3}$ is greater than or equal to the that of $LBP_{8.1}$ in laugh and surprise. It was found that the radius greater than 1 or 2 was useful for a specific emotion recognition. The facial expression recognition rate of proposed multi-scale LBP method was 97.5%. This showed the superiority of proposed method and it was confirmed through various experiments.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.384-386
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• 1998

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

• Journal of Korean society of Dental Hygiene
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• v.7 no.3
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• pp.285-299
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• 2007

The purpose of this study was to provide basic data of education program and consult for dental implant patient. The 210 of dental patients were selected at five dental clinic located in Jin-ju city. Data were collected by self-administrated questionnaire. A SPSS 10.10 for Windows was used for statistical analysis. The results of the study are summarized as follows: 1. The female responser was 56.2%, the rate of age was thirty years old 26.7%, education level was more than university and college 45.7%, job is company unit 15.2%, income was 100~200man won of 48.6%. 2. Recognition of dental implant was that incase of 'yes' is more than sixty years old 77.3%. 3. The information of implant was from neighborhood 29.0%, and when dental consult 24.3%. 4. The responsor who is everyone can take the dental implant operation is 39.5%, can not take is 32.9%. 5. The responsor who is everyone wants implant operation was 45.2%, 'do not' is 17.1%. 6. Using period of implant tooth is 'forever' 40.0%. In limited of twenty years' is 23.8%. 7. When everyone select to dental clinic was because of dentist medical technique is 64.3%, dental treatment cost is 15.9%. In conclusion, it is necessary for the dental implant patient to make dental consult and education program. So, try to study for make basic data with analysis recognition of dental implant patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4549-4566
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• 2017

This work presents a novel facial descriptor, which is named as multiscale adaptive local directional texture pattern (MALDTP) and employed for expression recognition. We apply an adaptive threshold value to encode facial image in different scales, and concatenate a series of histograms based on the MALDTP to generate facial descriptor in term of Gabor filters. In addition, some dedicated experiments were conducted to evaluate the performance of the MALDTP method in a person-independent way. The experimental results demonstrate that our proposed method achieves higher recognition rate than local directional texture pattern (LDTP). Moreover, the MALDTP method has lower computational complexity, fewer storage space and higher classification accuracy than local Gabor binary pattern histogram sequence (LGBPHS) method. In a nutshell, the proposed MALDTP method can not only avoid choosing the threshold by experience but also contain much more structural and contrast information of facial image than LDTP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.816-818
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• 2017

In this paper, we perform a performance analysis of a surveillance camera network system with an image recognition server based on frame discard rate and server utilization. Surveillance camera states are divided into recognition states and silence states to analyze the various parameters such as the optimum number of image frames and the optimum number of cameras based on the processing capacity of the server. The analyzed results will be useful for efficient operation of the evolving surveillance camera network systems.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3371-3381
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• 2010

In this study, quantitative and pattern recognition analysis for the quality evaluation of Magnoliae Flos using HPLC/UV was developed. For quantitative analysis, eleven major bioactive lignan compounds were determined. The separation conditions employed for HPLC/UV were optimized using ODS $C_{18}$ column ($250{\times}4.6\;mm$, $5\;{\mu}m$) with isocratic elution of acetonitrile and water with 1% acetic acid as the mobile phase at a flow rate of 1.0 mL/min and a detection wavelength of 278 nm. These methods were fully validated with respect to the linearity, accuracy, precision, recovery, and robustness. The HPLC/UV method was applied successfully to the quantification of eleven major compounds in the extract of Magnoliae Flos. The HPLC analytical method for pattern recognition analysis was validated by repeated analysis of twenty one reference samples corresponding to seven different species of Magnoliae Flos and nine samples purchased from market. The results indicate that the established HPLC/UV method is suitable for the quantitative analysis and quality control of multi-components in Magnoliae Flos.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.41-48
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• 2005

This paper presents a face recognition method based on the combination of well-known statistical representations of Principal Component Analysis(PCA), and Linear Discriminant Analysis(LDA) with Radial Basis Function Networks. The original face image is first processed by PCA to reduce the dimension, and thereby avoid the singularity of the within-class scatter matrix in LDA calculation. The result of PCA process is applied to LDA classifier. In the second approach, the LDA process Produce a discriminational features of the face image, which is taken as the input of the Radial Basis Function Network(RBFN). The proposed approaches has been tested on the ORL face database. The experimental results have been demonstrated, and the recognition rate of more than 93.5% has been achieved.