• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.900-904
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• 1991

In this paper, our study for the recognition of Hand-written Korean characters, Arabic numbers and alphabets by neural netwoks. This System extracts feature of character by using the MESH feature point of handwritten character, Arabic numbers and alphabets. To reduce the input image data, features are extracted from each input images. A MLP(multi-layer perceptron) with one hidden layer was trained with a modified BEP(back error propagation) algorithm. This method extracts feature sets of the characters directly from the scanner and can enhance computation speed without using the special preprocesses such as size normalization, smoothing, and thinning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.426-432
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• 2007

The MAP algorithm is designed and implemented through the sliding window method for turbo decoding. First, the implementation issues, which are the length of the sliding window and the normalization method of state metrics are reviewed, and their optimal values are obtained by the simulation. All component schemes of the decoder including the branch metric evaluator are also presented. The proposed MAP architecture can be easily redesigned according to the size of sliding window, that is, sub-frame length because of its simplicity on buffer control.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.245-252
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• 2002

The roughness of Joomoonjin sand and the Dongchun river sand was analysed by the fractal theory. It was found that the fractal dimension(D$\_$F/) of Joomoonjin sand is a little smaller than the Dongchun river sand. That means Joomoonjin sand is smoother than the Dongchun river sand. The measurements of D$\_$F/ of different fraction of the Donchun river sand showed that large particles were rougher than fine particles. The shapes of both sands were analysed by the Discrete Fourier Transform(DFT) and the Grid-based(GB) method. Normalization of coefficients with respect to size, starting point and its orientation made the coefficients invaried to these characteristics. The mean of the normalized coefficients was used to reconstruct the average shape for both sands, respectively. The measurements of the ellipticity ratio of different fraction of both sands showed that Joomoonjin sand is slightly flatter than the Dongcun river sand.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.130-134
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• 2020

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.111-118
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• 2019

Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.705-714
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• 2001

The computing systems of today expanded business trade and distributed business process Internet. More and more systems are developed from components with exactly reusability, independency, and portability. Component based development is focused on advanced concepts rater than passive manipulation or source code in class library. The primary component construction in CBD. However, lead to an additional cost for reconstructing the new component with CBD model. It also difficult to serve component information with rapidly and exactly, which normalization model are not established, frequency user logging in Web caused overload. A lot of difficult issues and aspects of Component Based Development have to be investigated to develop good component-based products. There is no established normalization model which will guarantee a proper treatment of components. This paper elaborates on some of those aspects of web application to adapt user requirement with exactly and rapidly. Distributed components in this paper are used in the most tiny size on network and suggest the network-addressable interface based on business domain. We also discuss the internal and external specifications for grasping component internal and external relations of user requirements to be analyzed. The specifications are stored on Servlets after dividing the information between session and entity as an EJB (Enterprise JavaBeans) that are reusable unit size in business domain. The reusable units are used in business component through query to get business component. As a major contribution, we propose a systems model for registration, auto-arrange, search, test, and download component, which covers component reusability and component customization.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.494-503
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• 2011

In this paper, we propose a recognition application of facial expression for laughter theraphy on smartphone. It detects face region by using AdaBoost face detection algorithm from the front camera image of a smartphone. After detecting the face image, it detects the lip region from the detected face image. From the next frame, it doesn't detect the face image but tracks the lip region which were detected in the previous frame by using the three step block matching algorithm. The size of the detected lip image varies according to the distance between camera and user. So, it scales the detected lip image with a fixed size. After that, it minimizes the effect of illumination variation by applying the bilateral symmetry and histogram matching illumination normalization. After that, it computes lip eigen vector by using PCA(Principal Component Analysis) and recognizes laughter expression by using a multilayer perceptron artificial network. The experiment results show that the proposed method could deal with 16.7 frame/s and the proposed illumination normalization method could reduce the variations of illumination better than the existing methods for better recognition performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3904-3922
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• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.3
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• pp.113-125
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• 2023

The COVID-19 pandemic has led to the normalization of mask-wearing worldwide, and young children are particularly vulnerable to respiratory diseases. Children's masks come in various sizes and shapes, causing confusion among consumers who struggle to find products that can accommodate their child's unique physical conditions. This research aims to analyze the shape and dimensions of health masks designed for young children. A total of 67 mask varieties were collected, and 58 were subjected to analysis. The masks were found to have two primary shapes: foldable and beak-like, with sizes categorized as small and extra-small. The majority of masks were manufactured in Korea, and the size labeling systems varied among manufacturers. The mask materials were non-woven fabric or polypropylene, and there was diversity in terms of the adjustable earbands and the use of additional accessories. The dimensions of the masks varied depending on their shape, with significant differences in the weight and the length of the wire holes. Subsequent research should focus on conducting wearability evaluations to verify the dimensional suitability of commercially available children's health masks based on shape and size. Additionally, this study aims to provide foundational data that can assist in the development of children's masks with size ranges that differentiate them from adult masks and cater to specific age groups.