• Journal of Korean society of Dental Hygiene
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• v.14 no.5
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• pp.609-615
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• 2014

Objectives : In most developed countries there has been a substantial decrease in the prevalence of dental caries in children of 12 years old over the past 40 years. This change in epidemiology highlights the importance of preventive management in dentistry. For successful management of early caries lesions, it is essential to detect and assess the pathological changes of dental caries. Therefore, the purpose of this study was to investigate the overview of International Caries Detection and Assessment System(ICDAS) criteria for the detection and assessment of early caries lesions by literature reviews. Methods : The author reviewed the MEDLINE search by the key words of 'caries assessment', 'caries detection', 'caries measurement', and 'ICDAS'. Results : This literature review provided an overview of International Caries Detection and Assessment System(ICDAS) criteria for the detection and assessment of early caries lesions. This article showed the principles, concept, and primary caries detection criteria of the ICDAS. The ICDAS can macroscopically measure the enamel surface changes and potential histological depth of caries lesions by the surface characteristics of the teeth. The ICDAS criteria allow researchers and clinicians to choose the stage of dental caries and characteristics for assessment. Conclusions : ICDAS can be an adjunct method to clinical decision making and preventive treatment planning.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.677-679
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• 1999

This paper introduces a implementation of fault detection for national highway line 3. Fault detection system was installed and operated on national highway line 3, environmental elements caused by abnormal status or faults has often happened. Therefore, the function of fault detection system is to speedy notify fault site, cause as well as scale of fault to manager. Though the fault detection and diagnosis system has been imported in the field of process of water and electric power, it is just beginning step in the field of ITS(Intelligent Transportation Systems). In general, Maintenance system is performed the online/offline process of detection, diagnosis and measure. This paper is studied online detection process, which is realtime remote detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4976-4994
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• 2018

The diffusion-based salient object detection methods have shown excellent detection results and more efficient computation in recent years. However, the current diffusion-based salient object detection methods still have disadvantage of detecting the object appearing at the image boundaries and different scales. To address the above mentioned issues, this paper proposes a multi-scale diffusion-based salient object detection algorithm with background and objectness seeds. In specific, the image is firstly over-segmented at several scales. Secondly, the background and objectness saliency of each superpixel is then calculated and fused in each scale. Thirdly, manifold ranking method is chosen to propagate the Bayessian fusion of background and objectness saliency to the whole image. Finally, the pixel-level saliency map is constructed by weighted summation of saliency values under different scales. We evaluate our salient object detection algorithm with other 24 state-of-the-art methods on four public benchmark datasets, i.e., ASD, SED1, SED2 and SOD. The results show that the proposed method performs favorably against 24 state-of-the-art salient object detection approaches in term of popular measures of PR curve and F-measure. And the visual comparison results also show that our method highlights the salient objects more effectively.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.1-10
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• 2018

This paper presents an autonomous detection and aiming point computation of a battle tank by using RGB images. Maximally stable extremal regions algorithm was implemented to find features of the tank, which are matched with images extracted from streaming video to figure out the region of interest where the tank is present. The median filter was applied to remove noises in the region of interest and decrease camouflage effects of the tank. For the tank segmentation, k-mean clustering was used to autonomously distinguish the tank from its background. Also, both erosion and dilation algorithms of morphology techniques were applied to extract the tank shape without noises and generate the binary image with 1 for the tank and 0 for the background. After that, Sobel's edge detection was used to measure the outline of the tank by which the aiming point at the center of the tank was calculated. For performance measurement, accuracy, precision, recall, and F-measure were analyzed by confusion matrix, resulting in 91.6%, 90.4%, 85.8%, and 88.1%, respectively.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1418-1421
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• 1987

An important problem in edge detection is to select a proper threshold that transforms the gradient picture to e two level picture containing optimum edges between regions, Such a threshold is determined depending on some measures of errors in tresholding. In this paper, an error criterion on extracting edges by thresholding the block gradient image is presented. Based on the error measure, the optimum threshold is chosen for the detection of acceptable edges.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1465-1468
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• 2006

We developed a new ellipsometer for MURA detection. This ellipsometer can measure MURA along the slit line on the sample with high sensitivity, because this ellipsometer irradiates a slit beam onto the sample but can reject the reflected light from the back surface of the substrate. This ellipsometer is suitable for measuring MURA of the surface of sample with high sensitivity.

• Journal of applied mathematics & informatics
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• v.5 no.3
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• pp.785-796
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• 1998

In this paper we propose a model of HIv population through method of phases with non-Markovian evolution of immi-gration. The analysis leads to an explicit differnetial equations for the generating functions of the total population size. The detection process of antibodies (against the antigen of virus) is analysed and an explicit expression for the correlation functions are provided. A measure of bunching is also introduced for some particular choice of parameters.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.29-32
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• 2002

This paper suggest target detection algorithm for mobile robot control using color and shape recognition. In many cases, ultrasonic sensor(USS) is used in mobile robot system to measure the distance between obstacles. But with only USS, it may have many restrictions. So we attached CCD camera to mobile robot to overcome its restrictions. If visual information is given to robot system then robot system will be able to accomplish more complex mission successfully. With acquired vision data, robot looks for target by color and recognize its shape.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.42-46
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• 2003

In this study, to measure the moisture of compaction, it is designed to use the 2neutron detectors. To perform the optimal design of their circuit, it is planned high voltage generator and voltage stable circuit and they are very suitable for detection demand. Also, it can be count to data calibration excluded count of ripple.