• The Journal of Korean Physical Therapy
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• 제24권4호
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• pp.262-267
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• 2012

Purpose: This study was designed to analyze the differences in cerebral cortex activity of the elderly after extracting the movement related cortical potentials (MRCPs) from electroencephalogram (EEG) during a concentric and eccentric contraction of the elbow joint flexors, and entering them into the brain-mapping program to make the images. Methods: Right-dominant normal elderly people were divided into an eccentric contraction group and a concentric contraction group. Then, their MRCPs were measured using EEG and sEMG, during an eccentric and concentric contraction. Then, they were converted into images using the brain-mapping program. Results: Eccentric contraction group's $C_3$ and Cz showed statistically higher mean values of MRCP positive potential than the concentric contraction group. Conclusion: Researching a cerebral cortex activity, using MRCP, would provide basic data for clinical neuro-physiological researches on aging or neural plasticity of patients with a central nervous system injury.

• 전자공학회논문지B
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• 제33B권8호
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• pp.68-80
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• 1996

In this paper, we propose a novel color image segmentation algorithm based on clustering in 3-dimensional color space employing the mathematical morphology. More specifically, since we take into account the topological properties such as the shape, connectivity and distribution of clusters in the clustering process, the number of clusters in the color cube, as well as their centers, can be easily obtained, without a priori knowledge on the input images. Intensive computer simulation has been performed and the results are discussed in this paper. The resutls of the simulation on the images in various color coordinates show that the segmentation is independent of the choice of color coordinates and the shape of clustes. Segmentation results of the vector quantizer are also presented for the comparison purpose.

• Geomechanics and Engineering
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• 제37권5호
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• pp.467-474
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• 2024

Monitoring and managing the condition of underground utilities is crucial for ground stability. This study aims to determine whether images obtained using ground penetrating radar (GPR) accurately reflect the characteristics of buried pipelines through image analysis. The investigation focuses on pipelines made from different materials, namely concrete and steel, with concrete pipes tested under various diameters to assess detectability under differing conditions. A total of 400 images are acquired at locations with pipelines, and for comparison, an additional 100 data points are collected from areas without pipelines. The study employs GPR at frequencies of 200 MHz and 600 MHz, and image analysis is performed using machine learning-based convolutional neural network (CNN) techniques. The analysis results demonstrate high classification reliability based on the training data, especially in distinguishing between pipes of the same material but of different diameters. The findings suggest that the integration of GPR and CNN algorithms can offer satisfactory performance in exploring the ground's interior characteristics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.418-420
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• 1993

In this paper, we proposed a new FMS Landmark recognition algorithm using color images. Firstly, a NTSC image fame is captured, and then it is converted to a field image in order to reduce the image blurring from the AGV motion. Secondly, the landmark is detected via the comparison of the color vectors of image pixels with the landmark color. Finally, the identification of FMS landmark is executed using a newly designed landmark pattern with a set of reference points. The landmark pattern is normalized against its translation, rotation, and scaling. And then, its vertical projection data are fisted for the pattern classification using the standard data set. Experimental results show that our scheme performs well.

• 대한치과교정학회지
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• 제40권6호
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• pp.364-372
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• 2010

본 연구는 교정 진단 및 치료 계획에 어려움을 줄 수 있는 측두 하악 관절 장애 증상을 보이는 환자의 cone beam computed tomography (CBCT) 영상과 파노라마 영상을 비교하여 파노라마 영상의 유용성을 알아보고자 하였다. 2008년 6월부터 2008년 11월까지 측두 하악 관절 부위의 이상 증상으로 치과 의원에 내원한 환자를 대상으로 임상 진단과 파노라마 촬영을 시행 후 CBCT로 촬영한 106명, 212개 관절을 대상으로 영상의 결과를 비교하였다. 2명의 치과의사가 하악 과두의 골변화의 양상을 관찰하여 정상(normal), 편평화(flattening), 골경화(sclerosis), 골증식체(osteophyte), 침식(erosion)으로 나누었다. 그 결과로 첫째, 검사자간 신뢰도에서 파노라마(weighted kappa: 0.714), CBCT (weighted kappa: 0.727) 각각의 영상 진단 일치도가 높았다. 둘째, CBCT 영상에 대한 파노라마 영상의 A 검사자의 민감도는 82.4%, 특이도는 58.1%였으며 B 검사자는 각각 84.3%, 61.5%였다. 셋째, 파노라마 영상과 CBCT 영상이 5% 유의수준에서 두 영상 간 판독이 동일하지 않았다. 이상의 결과는 파노라마 영상이 CBCT 영상과 비교할 때 비교적 높은 80% 이상의 민감도를 보여 측두 하악 관절 골 변화의 일차적인 진단수단으로 임상적으로 유용하게 사용될 수 있다는 것과 측두 하악 관절의 골 변화가 파노라마 영상에서 불분명한 경우 CBCT를 사용하였을 때 더욱 정밀한 진단이 될 수 있다는 것을 보여주었다.

• 대한핵의학회지
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• 제29권4호
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• pp.478-483
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• 1995

We compared the influences of reconstruction methods using $180^{\circ}$ or $360^{\circ}$ data upon contrasts and discriminating capability and diagnostic accuracy in $^{99m}Tc-MIBI$ stress/rest myocardial SPECT. We reviewed SPECT images reconstructed only with $180^{\circ}$ projection data or with $360^{\circ}$ data in 18 patients and in 11 normal subjects. To compare counts of surface structures and deep structures, we measured ape# posterior wall ratios in 11 normal subjects. To compare the contrasts of images, we measured apex/ventricle ratios. To compare contrasts between normal and diseased myocardial segments, we measured count ratios of defect and normal segments in 4 patients who had single coronary artery diseases. To compare diagnostic accuracy, we scored SPECT images made with $180^{\circ}$ and $360^{\circ}$ data segmentally. Sensitivity and specificity for the diagnosis of coronary artery disease and for the revelation of diseased arteries with both $180^{\circ}$ and $360^{\circ}$ SPECT images. If involved coronary arteries had more narrowing than 50% In coronary angiogram, we considered them as diseased arteries Apex/posterior wall ratios were not different significantly in normal subjects. Apex/ ventricle ratios in normal subjects were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images. Defect/normal ratios were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images in single vessel disease patients. The overall diagnostic accurracy was the same between $180^{\circ}$ and $360^{\circ}$ data collection. Sensitivity was 94% and specificity was 91% for both types of data collection in this sample population. Sensitivity and specificity of each coronary artery territory were not significantly different between the images made with $180^{\circ}$ and $360^{\circ}$ data. The images made with $180^{\circ}$ data had better contrast between ventricle and myocardium and between hypoperfused and normal myocardium, though no difference was found between the ratios of the myocardial counts of surface and deep structures. However, diagnostic sensitivities of diseased artery territories were not different significantly and so were overall diagnostic accuracy between both methods of making images with $180^{\circ}$ and $360^{\circ}$ data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.54-59
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• 1999

1999년 5월 26일에 발사된 우리별 3호는 고해상도 지구관측 센서가 담재되어 있으며, SPOT과 거의 유사한 분광대를 갖고 잇다. 따라서 본 보고에서는 우리별 3호에서 획득한 위성영상의 활용가능성을 확인하는 것을 주목적으로 하며, 현재 상용으로 제공되고 있는 대표적인 위성영상인 Landsat TM과 SPOT영상과 비교하는 것을 부목적으로 한다.

• Journal of Biosystems Engineering
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• 제24권4호
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• pp.325-334
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• 1999

The aim of this study was to present a groundwork for development of a sorting system of peeled garlics using machine vision. Images of various garlic samples such as sound, partially defective, discolored, rotten and un-peeled were obtained with a B/W machine vision system. Sorting factors which were based on normalized histogram and statistical analysis(STEPDISC Method) had good separability for various garlic samples. Bayes discriminant function and neural network sorting algorithms were developed with the sample images and were experimented on various garlic samples. It was showed that garlic samples could be classified by sorting algorithm with average sorting accuracies of 88.4% by Bayes discriminant function and 93.2% by neural network.

• 대한의용생체공학회:의공학회지
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• 제21권2호
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• pp.145-156
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• 2000

본 논문에서는 중앙시상 두뇌 자기공명영상 분할결과를 이용한 3차원 시상 두뇌 자기공명영상의 자동분할기법을 제안한다. 제안된 알고리즘에서는 먼저 3차원 시상 두뇌 자기공명영상의 중앙영상을 분할하고, 분할된 중앙두뇌 자기공명영상을 인접하는 영상에 마스크로 적용한다. 이 때 마스크 적용으로 인하여 인접하는 영상이 절단되는 문제가 발생할 수 있다. 이러한 문제를 해결하기 위하여 절단 영역의 경계점을 검출한 후, 절단 영역에 대한 경로 재설정을 통해 절단 영역을 복원한다. 이러한 경로 재설정을 위해 connectivity-based threshold segmentation algorithm을 사용하였다. 실험결과 제안된 알고리즘의 유용성을 확인할 수 있었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.835-838
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• 2000

Popular methods for extracting a text region in video images are in general based on analysis of a whole image such as merge and split method, and comparison of two frames. Thus, they take long computing time due to the use of a whole image. Therefore, this paper suggests the faster method of extracting a text region without processing a whole image. The proposed method uses line sampling methods, FFT and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 92% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image, and fast skipping of the images that do not contain a text.