• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.973-982
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• 2003

This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.37-48
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• 2005

In this paper, a new object detection method for FLIR images is proposed. The proposed method consists of intensity ranking feature and a classification algerian using the feature. The intensity ranking feature is a representation of an image, from which intensity distribution is regularized. Each object candidate region is classified as object or non-object by the proposed classification algorithm which is based on the intensity ranking similarity between the candidate and object training images. Using the proposed algorithm pixel-wise detection results can be obtained without any additional candidate selection algorithm. In experimental results, it is shown that the proposed ranking feature is appropriate for object detection in a FLIR image and some vehicle detection results in the situation of existing noise, scale variation, and rotation of the objects are presented.

• Cartoon and Animation Studies
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• s.49
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• pp.383-398
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• 2017

Virtual Reality contents are being used as media in various fields. In order for the virtual reality contents to be realistic, the scale of the objects in the virtual reality must be the same as the actual size, and the user must feel the same size. However, even if the size of the character in the virtual reality space is made equal to the size in comparison with the size of the character in the reality, the distortion of the size can occur when the user looks at the object in the image with the HMD. In this paper, I investigate the requirements related to size in virtual reality, and try to find out what difference these requirements have in virtual reality and how the difference affects users. Experiments and surveys to compare the size of objects in virtual reality space and the size of objects in real space were conducted to investigate how scale distortion occurs at distant and near places. I hope that this paper will be a useful research for virtual reality developers.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.286-288
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• 2006

영상 이해는 컴퓨터 비전의 가장 높은 수준의 처리 기법이다. 영상을 이해하기 위해서는 위치 정보, 물체 존재정보와 같은 기본 컨텍스트들을 추출하는 것이 중요하다. 그러나 실내 환경의 영상 정보는 카메라의 흔들림이나 각도, 빛의 상태에 따라 불확실해지기 때문에 이러한 불확실함에 강인한 영상 인식 기법이 필요하다. 동적 베이지안 네트워크(DBN)는 이러한 불확실한 정보의 처리에 강인하며 장소와 물체의 관계등 고수준의 컨텍스트를 모델링하는데 좋은 성능을 보이는 확률 모델이다. 또한 DBN은 이전 상태를 추론에 활용할 수 있으므로 장소 인식과 같은 컨텍스트의 추출에 좋다. 본 연구에서는 불확실한 실내 환경 영상으로부터 영상 전처리를 통해 특징값을 추출하고, 회전이나 크기 변화에 강인한 물체인식기법인 크기불변 특징 변환기법(SIFT)을 이용하여 물체 존재정보를 추출하여 고수준 컨텍스트가 모델링된 DBN 추론으로 장소 및 물체를 인식하는 방법을 제안한다. 실제 대학 실내 환경에서의 실험으로 DBN을 이용한 영상 인식기법이 좋은 성능을 보임을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.111-113
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• 2005

지하에 매설된 가스관의 경우 MFL(Magnetic Fluk Leakage, 자기누설탐상) PIG를 이용하여 금속관의 여러 가지 기계적인 손상을 감지하여 사고예방이나 유지관리의 정보로 활용하고 있다. 이러한 비파피검사는 당장 수리가 필요한 손상에서부터 장래에 위협이 될 수도 있는 지하 매설관 외부의 금속물체(Metal object)까지 찾아낼 수 있어야 한다. 이 논문은 지하 매설관 외부의 금속물체의 크기, 모양 및 이격거리 등에 따른 자기누설 신호를 유한요소법을 이용하여 simulation 하고, MFL PIG를 이용하여 지하 매설관에 대한 비파괴검사를 할 경우 나타나는 여러 가지 자기적 신호를 보정하여 metal object의 크기나 위치 등을 판별할 수 있도록 기본적인 자기누설 정보를 제공하기 위한 연구이다. NMFL PIG의 형상과 금속물체의 크기 종류 의 정확한 분석을 위하여 3차원 해석을 하였다.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.539-548
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• 2001

In this paper, we propose that fast tracking algorithm for moving object is separated from background, using partial boundary line information. After detecting boundary line from input image, we track moving object by using the algorithm which takes boundary line information as feature of moving object. we extract moving vector on the imput image which has environmental variation, using high-performance BMA, and we extract moving object on the basis of moving vector. Next, we extract boundary line on the moving object as an initial feature-vector generating step for the moving object. Among those boundary lines, we consider a part of the boundary line in every direction as feature vector. And then, as a step for the moving object, we extract moving vector from feature vector generated under the information of the boundary line of the moving object on the previous frame, and we perform tracking moving object from the current frame. As a result, we show that the proposed algorithm using feature vector generated by each directional boundary line is simple tracking operation cost compared with the previous active contour tracking algorithm that changes processing time by boundary line size of moving object. The simulation for proposed algorithm shows that BMA operation is reduced about 39% in real image and tracking error is less than 2 pixel when the size of feature vector is [$10{\times}5$] using the information of each direction boundary line. Also the proposed algorithm just needs 200 times of search operation bout processing cost is varies by the size of boundary line on the previous algorithm.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.1
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• pp.51-61
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• 2020

Objectives : The purpose of this study is to investigate the effect of object size and reaching distance on kinematic factors of the upper limb while performing arm reaching for normal subjects. Methods : The subjects of this study were 30 university students who were in D university in Busan, and the measuring tool was CMS-70P(Zebris Medizintechnik Gmbh, Germany), a three-dimensional motion analyzer. The task had six conditions. The average velocity of motion, average acceleration, maximum velocity, and the velocity definite number of movements were measured according to changes in object size(2cm, 10cm) and reaching distance(15%, 37.5%, 60%) when they performed arm reaching. The general characteristics of the subject were technical statistics. One-way ANOVA measurement was used to compare variables when the arm reaching task was performed from two object sizes to three reaching distance, and the post-test was conducted with Tukey test. In addition, an independent t-test was used to analyze the kinematic differences according to the two object sizes at three reaching distances. A two-way ANOVA measurement (3×2 Two-way ANOVA measurement) was performed to identify the interaction of the reaching distance(15%, 37.5%, 60%) and the object size(2cm, 10cm). The statistical significance level α was set to .05. Results : When the size of the object increased, the velocity and maximum velocity also increased, but the definite number of velocity decreased. When the reaching distance increased, the velocity and maximum velocity increased, whereas the definite number of velocity decreased. Conclusion : The clinical significance of this study could be utilized as the baseline data for grading object size and reaching distances when the reaching training is implemented for patients whose central nervous system was damaged.

• Journal of KSNVE
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• v.8 no.6
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• pp.1172-1180
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• 1998

Elastic wave scattering from an acoustically rigid or soft object is studied and compared with the acoustic wave scattering. The behavior of phases as well as magnitudes of partial waves and their total summation of scattered wave are numerically analyzed and discussed. The effect of mode conversion, which occurs between longitudinal and transversal waves in elastic wave scattering. on the magnitudes and phases of scattered waves is identified.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.197-202
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• 2006

본 논문에서는 퍼지 신경회로망을 사용하여 영상에서 물체를 배경으로부터 추출해내는 방법을 제시하였다. 퍼지 신경회로망의 vigilance parameter를 조정하여 영상을 2개의 클래스로 분류하고, 물체 영역과 배경영역의 Cb와 Cr의 대표값을 추출하였다. 제안한 방법을 사용하여 물체색상의 위치 및 크기와 밝기에 상관없이 물체영역을 추출하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.125-128
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• 2007

최근에 지능형 로봇분야에서 주위 카메라를 기반으로 실시간으로 환경인식 및 물체 추적 등 다양한 분야에서 연구가 활발히 진행되고 있다. 환경인식 및 물체 추적은 결국 배경과 관심물체를 분리하는 것이라고 볼 수 있는 데, 차 연산을 이용하여 물체의 움직임만을 배경으로 분리하는 방법과 물체인식을 통해 배경으로부터 분리하여 추적하는 방법에 대한 연구가 지속적으로 이루어지고 있다. 본 논문에서는 배경과 물체 사이에서 변화하는 색상의 변화를 퍼지기법을 이용하여 물체를 배경과 분리하여 실시간으로 물체를 추적하고자 한다. 실시간 물체 추적을 위해 전체영상에 대한 전역적 탐색을 통해 여러 후보 물체 중 관심물체를 배경에서 추출 후, 추출된 물체의 크기에 따른 지역탐색을 통하여 물체를 추적하는 방법이다. 그리고 본 논문에서는 ARM프로세서를 이용한 카메라시스템을 제작하여 실시간 추적을 실험하였다.