• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.19-22
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• 2000

This paper presents new on-line handwritten algorithm for continuous alphabet uppercase characters. The algorithm is based on the idea that alphabet uppercase character consists of at most 4 strokes. It tries to determine the maximum output for a recognition result among outputs of four recognizers which have the capacity to discriminate the character using from 1 through 4 stroke information. The recognition module has 4 neural network based recognizers, which can recognize from 1 through 4 stroke character. We also use specialized post-processing techniques for improving the recognition performance. Trained on 440 input data and choosing 390 uppercase words for a recognition test we reached a 92% recognition rate.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.121-126
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• 2002

The stereoscopic image is that we can see it closer than a real thing compared to 2D image, and it has influence on human's vision information because it is more natural method to feel connections between the spaces of the image and himself. There are several method convert from 2d image to 3d image. But, in this paper, we are propose the image separate algorithm of continuous input system through a spatial analysis, not be done with 2D still image. Additionally, we will adapt to the moving vector which has been used in MPEG. In this experiment, we obtained the effect of 3D image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.166-174
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• 1994

This paper presents the algorithm of an on-line cursive Hangeul recognition by means of the DP matching with structural information. In the proposed method, the penalty represents the similarity between input character and reference character. The penalty is dynamically computed with types of strokes, directions of strokes, and the length rations of fragment during the process that searchs for an optimal path using 3$\times$3 matrix. As the result, this method can be exactly matched for even greatly deformed characters. The computer simulation shows that the proposed algorithm can be utilized in recognizing cursive Hangeul as well as correct Hangeul.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.7
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• pp.101-108
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• 1998

In this paper, after we got to realized FDNN (fuzzy decision neural network) applied the quantization triangularity fuzzy function to DBNN(decision based neural network) of a hierarchical structure for image process, we could esign hardware of the realized FDNN. Also it is normalized the standard image and the input image as the same size. We are applied DWW algorithm which selected the closest value with finding similarity of an interval image by this distance to FDNN. So we could calulated in terms of distance to weight of pixel which composed two image and eliminated the nise of image, minimized the lost of information, obtained the optimal information. It is designed hardware of high speed weighted FDNN using COMPASS tool. Aslo, the total circuit is realized as gates of 61,000 and could show to superiority of FDNN using the simulation.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1957-1958
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• 2008

The Logic Built In Self Test (LBIST) technique is substantially applied in chip design in most many semiconductor company in despite of unavoidable overhead like an increase in dimension and time delay occurred as it used. Currently common LBIST software uses the MISR (Multiple Input Shift Register) However, it has many considerations like defining the X-value (Unknown Value), length and number of Scan Chain, Scan Chain and so on for analysis of result occurred in the process. So, to solve these problems, common LBIST software provides the solution method automated. Nevertheless, these problems haven't been solved automatically by Tri-state Bus in logic circuit yet. This paper studies the simulator and algorithm that judges whether Tri-state Bus lines is the circuit which have X-value or One-hot Value after presuming the control signal of the lines which output X-value in the logic circuit to solve the most serious problems.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1952-1954
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• 2001

In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through comparing with ANFIS.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.19-26
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• 2008

In this paper, we converted an RGB into an YCbCr image input from CCD camera and then after compute difference two consecutive images, conduct Glassfire Labeling. We extract an image become ware of motion-change, if the difference between most broad(area) and Area critical value more than critical value. We enforce the detection of facial characteristics to an extracted motion-change images by using AdaBoost algorithm to extract an characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.197-200
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• 2014

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image. The proposed method produces good results of facial expression and discriminates risk situation well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4463-4482
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• 2020

Mesh model generated from 3D reconstruction usually comes with lots of noise, which challenges the performance and robustness of mesh simplification approaches. To overcome this problem, we present a novel method for mesh simplification which could preserve structure and improve the accuracy. Our algorithm considers both the planar structures and linear features. In the preprocessing step, it automatically detects a set of planar structures through an iterative diffusion approach based on Region Seed Growing algorithm; then robust linear features of the mesh model are extracted by exploiting image information and planar structures jointly; finally we simplify the mesh model with plane constraint QEM and linear feature preserving strategies. The proposed method can overcome the known problem that current simplification methods usually degrade the structural characteristics, especially when the decimation is extreme. Our experimental results demonstrate that the proposed method, compared to other simplification algorithms, can effectively improve the quality of mesh and yield an increased robustness on noisy input mesh.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.243-250
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• 2004

We describe a practical implementation of DVR (Digital Video Recording) system. And we propose a new image compression algorithm, that input video signal is divided into two parts, a moving target and a non-moving background part to achieve efficient compression of image sequences. This algorithm reorganizes a target area and a back-ground area by use of Macro Block(MB) unit on encoding scheme. The proposed algorithm allows high quality image reconstruction at low bit rates.