• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.819-822
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• 2000

The merit of the stroke extraction algorithm is the ease of the feature abstraction from the skeleton of a character, But, extracting strokes from Korean characters has two major problems that must be dealt with. One is extracting primitive strokes and the other is merging or splitting the strokes using dynamic information of the strokes. In this paper, a method is proposed to extract strokes from an off-line handwritten Korean character. We have developed some stroke segmentation rules based on splitting, merging and directional analysis. Using these techniques, we can extract and trace the strokes in an off-line handwritten Korean character accurately and efficiently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.530-536
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• 2020

The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.598-605
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• 2018

Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.473-480
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• 2014

As the use of computer has been popularized these days, an active research is in progress to make much more convenient and natural interface compared to the existing user interfaces such as keyboard or mouse. For this reason, there is an increasing interest toward Microsoft's motion sensing module called Kinect, which can perform hand motions and speech recognition system in order to realize communication between people. Kinect uses its built-in sensor to recognize the main joint movements and depth of the body. It can also provide a simple speech recognition through the built-in microphone. In this paper, the goal is to use Kinect's depth value data, skeleton tracking and labeling algorithm to recognize information about the extraction and movement of hand, and replace the role of existing peripherals using a virtual mouse, a virtual keyboard, and a speech recognition.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.175-180
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• 2018

In this paper, a feature extraction and object recognition algorithm using only morphological operations is proposed. The morphological operations used in feature extraction are erosion and dilation, opening and closing combining erosion and dilation, and morphological edge and skeleton detection operation. In the process of recognizing an object based on features, a pooling operation is applied to reduce the dimension. Among various structuring elements, $3{\times}3$ rhombus, $3{\times}3$ square, and $5{\times}5$ circle are arbitrarily selected in morphological operation process. It has confirmed that the proposed algorithm can be applied in object recognition fields through experiments using Internet images.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.977-984
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• 2022

Recently, with the economic development of Southeast Asia, the use of information devices is widely spreading, and the demand for application services using intelligent character recognition is increasing. This paper discusses deep learning-based feature extraction and recognition of Myanmar, one of the Southeast Asian countries. Myanmar alphabet (33 letters) and Myanmar numerals (10 numbers) are used for feature extraction. In this paper, the number of nine features are extracted and more than three new features are proposed. Extracted features of each characters and numbers are expressed with successful results. In the recognition part, convolutional neural networks are used to assess its execution on character distinction. Its algorithm is implemented on captured image data-sets and its implementation is evaluated. The precision of models on the input data set is 96 % and uses a real-time input image.

• The korean journal of orthodontics
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• v.26 no.4
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• pp.349-358
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• 1996

To extract or not to extract permanent teeth for the correction of malocclusion has been a great debate in the history of orthodontics, and there is a variety of analytic methods and criteria to aid in the diagnosis. Extraction formulas that has been presented are many analytic methods that depend on arch length discrepancy, dental prominence, and skeletal pattern of the each patients. Of these analysis, the most important diagnostic factor is patient's skeletal pattern. Because the behavior of the dentition is closely dependent upon the skeletal pattern of each patient, dentition must be arranged within that person's skeletal frame. EI(Extraction Index) is composed of CF, interincisal angle, and lip position. CF is made of ODI and APDI that differentiate vertical and horizontal component of the skeletal pattern. So, EI not only represents patient's skeletal pattern, but also takes facial appearance into consideration. This study was undertaken to investigate EI and related cephalometric variables on the cephalogram of Korean adolescents which consisted of 153 persons with normal occlusion, harmonious skeleton and pleasing face. The following conclusions were obtained. 1. The mean value of the ODI is $73.5^{\circ}$, APDI $82.5^{\circ}$, CF $156.3^{\circ}$ 2. The mean value of the interincisal angle is $123.6^{\circ}$ 3. The mean distance of upper lip to E-line is 0.0mm, lower lip to E-line is 1.4mm. 4. The mean value of the EI is $153.8^{\circ}$.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.700-702
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• 2005

3차원 관상동맥처럼 위상 구조가 중요한 객체의 형상을 분석하기 위해서는 혈관의 분기점, 극단점, 혈관의 계층적 구조 관계 등의 정보를 함축적으로 표현할 수 있는 골격 추출이 매우 중요하다 본 논문에서는 3차원 CT 혈관조영술(3D CT Angiography)로 촬영된 영상으로부터 관상동맥의 3차원 골격을 추출하는 방법을 개발하였다. 먼저, CT 혈관조영술부터 획득한 슬라이스 이미지로부터 3차원 조작 및 수술 시뮬레이션 등을 위하여 혈관의 3차원 표면에 대한 메쉬 모델을 생성한다. 생성된 메쉬 모델이 임의로 변형된 후에도 자동으로 골격을 쉽게 추출할 수 있도록 메쉬 모델을 복셀화하는 단계를 거친다. 이렇게 얻어진 복셀모델로부터 유클리디언 거리 맵을 구성하여 discrete medial surface (DMS)을 생성하고 최종적으로 골격을 추출하게 된다. 이렇게 추출된 3차원 골격은 관상동맥 수술 시뮬레이션 등에서 다양한 형상 분석에 유용하게 사용될 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.275-280
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• 2008

본 논문에서는 한글 글립(glyph)의 형태학적 분석을 통해 자동으로 획을 분할하는 방법을 제안한다. 제안된 방법은 thinning된 한글 글립의 골격(skeleton) 이미지를 기반으로, 획 분리, 획 병합, 그리고 획 볼륨 복원의 세가지 단계를 거쳐 한글의 기본 획들을 추출해 낸다. 실험 결과, 트루타입폰트(TrueType Font)에 대해서는 80%, 손글씨(Handwriting) 글립에 대해서는 72%의 획 분할 정확도를 보였다. 본 논문에서 제안한 방법으로 획득된 획 정보를 이용하여, 향후 한글 손글씨 생성을 위한 연구를 하고자 한다.

• Journal of the Korea Society for Simulation
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• v.4 no.1
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• pp.1-11
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• 1995

The model of a FMS (Flexible Manufacturing System) admits to a natural hierarchical decomposition of highly decoupled units with similar structure and control. The FMS fractal architecture model represents a hierarchical structure built from elements of a single basic design. A SES (System Entity Structure) is a structural knowledge representation scheme that contains knowledge of decomposition, taxonomy, and coupling relationships of a system necessary to direct model synthesis. A substructure of a SES is extracted for use as the skeleton for a model. This substructure is called pruned SES and the extraction operation of a pruned SES from a SES is called pruning (or pruning operation). This paper presents a pruning operation called recursive pruning. It is applied to SES for generating a model structure whose sub-structure contains copies if itself as in FMS fractal architecture. Another pruning operation called delay pruning is also presented. Combined with recursive pruning the delay pruningis a useful tool for representing and constructing complex systems.