• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.1-10
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• 2005

In this Paper, we propose a new block matching a1gorithm that extracts motion vectors from consecutive range data. The proposed method defines a matching metric that integrates intensity, hue, and range. Our algorithm begins matching with a small matching template. If the matching degree is not good enough, we slightly expand the size of a matching template and then repeat the matching process until our matching criterion is satisfied or the predetermined maximum size has been reached. As the iteration proceeds, we adaptively adjust weights of the matching metric by considering the importance of each feature. In the experiments, we show that our block matching approach can work as a promising solution by comparing the proposed method with previously known method in terms of performance.

• The Plant Pathology Journal
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• v.19 no.3
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• pp.159-161
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• 2003

The coat protein (CP) gene of Apple mosaic virus (ApMV), a member of the genus Ilarvirus, was selected for the design of virus-specific primers for amplification and molecular detection of the virus in cultivated apple. A combined assay of reverse transcription and polymerase chain reaction (RT-PCR) was performed with a single pair of ApMV-specific primers and crude nucleic acid extracts from virus-infected apple for rapid detection of the virus. The PCR product was verified by restriction mapping analysis and by sequence determination. The lowest concentration of template viral RNA required for detection was 100 fg. This indicates that the RT-PCR for detection of the virus is a 10$^3$times more sensitive, reproducible and time-saving method than the enzyme-linked immunosorbent assay. The specificity of the primers was verified using other unrelated viral RNAs. No PCR product was observed when Cucumber mosaic virus (Cucumovirus) or a crude extract of healthy apple was used as a template in RT-PCR with the same primers. The PCR product (669 bp) of the CP gene of the virus was cloned into the plasmid vector and result-ant recombinant (pAPCP1) was selected for molecule of apple transformation to breed virus-resistant transgenic apple plants as the next step. This method can be useful for early stage screening of in vitro plantlet and genetic resources of resistant cultivar of apple plants.

• Smart Media Journal
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• v.4 no.4
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• pp.9-17
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• 2015

Recently the need for advanced security technologies are increasing as the occurrence of intelligent crime is growing fastly. Previous liveness detection and fake face detection methods are required for the improvement of accuracy in order to be put to practical use. In this paper, we propose a new liveness detection method using pupil reflection, and new fake image detection using Adaboost detector. The proposed system detects eyes based on multi-scale Gabor feature vector in the first stage, The template matching plays a role in determining the allowed eye area. And then, the reflected image in the pupil is used to decide whether or not the captured image is live or not. Experimental results indicate that the proposed method is superior to the previous methods in the detection accuracy of fake images.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.233-242
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• 1998

In anatomical aspects, magnetic resonance image offers more accurate information than other medical images such as X ray ultrasonic and CT images. This paper introduces a method that recognizes disk diseases from spine MR images. In this method, image enhancement, image segmentation and feature extraction for sagittal plane and axial plane images are performed to separate the disk region. And then template matching method is used to extract disease region for axial plane imges. Finally, disease feature vectors are integrated and disease discrimination processes are performed. Experimental results show that the proposed method discriminates between normal and diseased disk with a considerable recognition ratio.

• Journal of Life Science
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• v.15 no.6 s.73
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• pp.923-927
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• 2005

ln order to develop yeast cells that produce a bacteriocin on their cell surfaces, the 114 bp Leucocin A gene with stop codon was ligated into pYDl, an yeast vector. The recombinant DNA, pYDl-LeucoA was used to transform yeast (Saccharomyces cerevisiae) cells. Yeast cells harboring pYDl-LeucoA showed antibacterial activity against Bacillus subtilis. To confirm these bacteriocidal yeast cells possess the Leucocin A gone, PCR was performed with plasmid prepared from transformed yeast cells as a template and two Leucocin A-specific primers. In this study, bacteriocidal yeast cells that can be used as an antibiotic or a food preservative were developed.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.3
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• pp.244-249
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• 2015

With the recent progress of digital technology, the computer guided surgery utilizing a guide template in the placement of implant has been actively performed, and the method employing the intraoral scanner at the implant prosthesis introduced. Fabrication method of the guide template can be largely classified into design-related rapid prototyping (RP) system and vector milling system, and each of the method has its own weakness in the clinical application despite of excellent accuracy. Thus, in this case study, a working model was fabricated by the wax RP technology using images acquired by CBCT and an intraoral scanner, and the metal bushing was picked up with orthodontic resin cast upon the wax model. Using this method, a surgical guide template was fabricated and used in surgery. From this, we could obtain a satisfactory outcome clinically in the implant placement and the fabrication of the final prostheses and thus report this case herein.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.645-651
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• 2010

Recently the need for advanced security technologies are increasing as the occurrence of intelligent crime is growing fastly. Previous liveness detection methods are required for the improvement of accuracy in order to be put to practical use. In this paper, we propose a new fake image detection method using pupil reflection. The proposed system detects eyes based on multi-scale Gabor feature vector in the first stage, and uses template matching technique in oreder to increase the detection accuracy in the second stage. The template matching plays a role in determining the allowed eye area. The infrared image that is reflected in the pupil is used to decide whether or not the captured image is fake. Experimental results indicate that the proposed method is superior to the previous methods in the detection accuracy of fake images.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.162-168
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• 2008

A look-up table based vector adaptive filter is proposed in color inverse halftoning. Inverse halftoning converts halftone image into a continuous-tone image. The templates and training images are required in the process of look-up table based methods, which can be obtained from distributed patterns in the sample halftone images and their original images. Although the look-up table based methods usually are faster and show better performances in PSNR than other methods do, they show wide range of qualities depending on how they treat nonexisting patterns in the look-up table. In this paper, a vector adaptive filter is proposed to compensate for these nonexisting patterns, which achieves better quality owing to the contributed informations about hue, saturation, and intensity of surrounding pixels. The experimental results showed that the proposed method resulted in higher PSNR than that of conventional Best Linear Estimation method. The bigger the size of the template in the look-up table becomes, the more outstanding quality in the proposed method can be obtained.

• ETRI Journal
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• v.32 no.5
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.133-138
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• 2003

The prediction of protein secondary structure has been an important bioinformatics tool that is an essential component of the template-based protein tertiary structure prediction process. It has been known that the predicted secondary structure information improves both the fold recognition performance and the alignment accuracy. In this paper, we describe several novel ideas that may improve the prediction accuracy. The main idea is motivated by an observation that the protein's structural information, especially when it is combined with the evolutionary information, significantly improves the accuracy of the predicted tertiary structure. From the non-redundant set of protein structures, we derive the 'potential' parameters for the protein secondary structure prediction that contains the structural information of proteins, by following the procedure similar to the way to derive the directional information table of GOR method. Those potential parameters are combined with the frequency matrices obtained by running PSI-BLAST to construct the feature vectors that are used to train the support vector machines (SVM) to build the secondary structure classifiers. Moreover, the problem of huge model file size, which is one of the known shortcomings of SVM, is partially overcome by reducing the size of training data by filtering out the redundancy not only at the protein level but also at the feature vector level. A preliminary result measured by the average three-state prediction accuracy is encouraging.