• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.37-43
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• 2015

In this paper, a new background subtraction algorithm for video based fence monitoring surveillance systems is proposed. We adopt the sampling based background subtraction technique and focus on the two main issues: handling highly dynamic environment and handling the flickering nature of pulse based IR (infrared) lamp. Natural scenes from fence monitoring system are usually composed of several dynamic entities such as swaying trees, moving water, waves and rain. To deal with such dynamic backgrounds, we utilize the confidence factor for each background value of the input image. For the flickering IR lamp, the original sampling based technique is extended to handle double background models. Experimental results revealed that our method works well in real fence monitoring surveillance systems.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.56-66
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• 2001

The spectral subtraction algorithm using a criterion based on the human perception has been recently developed. The speech processed with Virag's algorithm sounds more pleasant to a human listener than those obtained by the classical methods. However, Virag's algorithm requires a robust voice activity detector (VAD). In the ESS (extended spectral subtraction) algorithm without VAD, the residual noise becomes more noticeable as the SNR decrease. In this paper we propose a new speech enhancement method, the combination of Wiener filter and spectral subtraction based on noise masking characteristics in the human auditory system. There is no need of VAD because the noise can be successively updated even during speech activity using Wiener filter. The adjustment of the subtraction parameter based on the masking threshold makes the residual noise inaudible. The proposed method has been compared with conventional spectral subtraction algorithms. Objective and subjective evaluation of the proposed system is performed with several noise types having different time-frequency distributions. The application of objective measures, the study of the speech spectrograms, as well as subjective listening tests, confirm that the enhanced speech with proposed algorithm is more pleasant to a human listener.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.108-115
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• 2013

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. In this field, area for technique can be divided into Foreground Subtraction which detects individuals and objects in a potential observing area and a tracing technology which figures out moving route of individuals and objects. In this thesis, an improved algorism for a settled engine development, which is stable to change in both noise and illumination for detecting moving objects is suggested. The proposed algorism from this thesis is focused on designing a stable and real time processing method which is perfect model in detecting individuals, animals, and also low-speeding transports and catching a change in an illumination and noise.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.275-280
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• 2004

In this paper, we propose automatic subtraction radiography algorithms to overcome conventional subtraction radiography's defects by applying image processing technique. In order to reach these goals, this paper suggests the image alignment method that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the structure characteristics in target images. Therefore, we use these methods because they give accurary, consistency and objective information or data to results. According to the results, easily and visually we can identify fine difference int the affected parts wether they have problems or not.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1146-1156
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• 2021

Single-unit probabilistic safety assessment (SUPSA) has complex Boolean logic equations for accident sequences. Multi-unit probabilistic safety assessment (MUPSA) model is developed by revising and combining SUPSA models in order to reflect plant state combinations (PSCs). These PSCs represent combinations of core damage and non-core damage states of nuclear power plants (NPPs). Since all these Boolean logic equations have complemented gates (not gates), it is not easy to generate exact Boolean solutions. Delete-term approximation method (DTAM) has been widely applied for generating approximate minimal cut sets (MCSs) from the complex Boolean logic equations with complemented gates. By applying DTAM, approximate conditional core damage probability (CCDP) has been calculated in SUPSA and MUPSA. It was found that CCDP calculated by DTAM was overestimated when complemented gates have non-rare events. Especially, the CCDP overestimation drastically increases if seismic SUPSA or MUPSA has complemented gates with many non-rare events. The objective of this study is to suggest a new quantification method named probability subtraction method (PSM) that replaces DTAM. The PSM calculates accurate CCDP even when SUPSA or MUPSA has complemented gates with many non-rare events. In this paper, the PSM is explained, and the accuracy of the PSM is validated by its applications to a few MUPSAs.

• Imaging Science in Dentistry
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• v.32 no.3
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• pp.147-151
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• 2002

Purpose: To compare the standard deviation of gray levels on digital subtracted images obtained by different dental subtraction programs. Materials and Methods: Paired periapical films were taken at the lower premolar and molar areas of the phantoms involving human mandible. The bite registration group used Rinn XCP equipment and bite registration material, based on polyvinyl siloxane, for standardization. The no bite registration group used only Rinn XCP equipment. The periapical film images were digitized at 1200 dpi resolution and 256 gray levels by a flat bed scanner with transparency unit. Dental digital subtraction programs used for this study were Subtractor (Biomedisys Co., Korea) and Emago (Oral Diagnostic Systems, The Netherlands). To measure the similarities between the subtracted images, the standard deviations of the gray levels were obtained using a histogram of subtracted images, which were then analyzed statistically. Results: Subtracted images obtained by using the Emago program without manual selection of corresponding points showed the lowest standard deviation of gray levels (p<0.01). And the standard deviation of gray levels was lower in subtracted images in the group of a bite registration than in the group of no use of bite registration (p < 0.01). Conclusion: Digital radiographic subtraction without manual selection of reference points was found to be a convenient and superior method.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.151-156
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• 2018

In this paper, a method to classify objects in outdoor CCTV images using Convolutional Neural Network(CNN) and background subtraction is proposed. Object candidates are extracted using background subtraction and they are classified with CNN to detect objects in the image. At the end, computation complexity is highly reduced in comparison to other object detection algorithms. A database is constructed by filming alleys and playgrounds, places where crime occurs mainly. In experiments, different image sizes and experimental settings are tested to construct a best classifier detecting person. And the final classification accuracy became 80% for same camera data and 67.5% for a different camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1946-1963
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• 2014

Most background subtraction methods focus on dynamic and complex scenes without considering robustness against noise. This paper proposes a background subtraction algorithm based on dictionary learning and sparse coding for handling low light conditions. The proposed method formulates background modeling as the linear and sparse combination of atoms in the dictionary. The background subtraction is considered as the difference between sparse representations of the current frame and the background model. Assuming that the projection of the noise over the dictionary is irregular and random guarantees the adaptability of the approach in large noisy scenes. Experimental results divided in simulated large noise and realistic low light conditions show the promising robustness of the proposed approach compared with other competing methods.

• Journal of Korean Medical classics
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• v.28 no.2
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• pp.103-114
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• 2015

Objectives : The publication year(1608) of Euilinchwalyo is very closed to the year(1610) of Dongeuibogam, so several researches indicate that Dongeuibogam was influenced by Euilimchwalyo. We, authors have recently focused on the way to quote books in Dongeuibogam and found particular aspects in the way of quotation between Euilimchwalyo and Dongeuibogam. Methods : 1. Comparing the contents of Sosokmyeongtang in quotation books between Euilimchwalyo and Dongeuibogam. 2. Tracing the origin of Sosokmyeongtang and comparing chief virtue, consist of herbal medicine, way of dose and making and the method of addition and subtraction in Sosokmyeongtang. Results : Beijiqianjiyaofang was the origin book that recorded Sosokmyeongtang but there was no methods of addition and subtraction. After Jin and Yuan dynasty, the books, which had Sosokmyeongtang, started to record the methods of addition and subtraction in Sosokmyeongtang. However, even though Euilinchwalyo also recorfed the methods of addition and subtraction in Sosokmyeongtang such as other medical books, Dongeuibogam didn't keep that way to document up. Conclusions : The fact that Dongeuibogam was influenced by Euilimchwalyo means 2 ways. The first is that Dongeuibogam was influenced by Euilimchwalyo directly. The second is that Heo Jun, who wrote Dongeuibogam, tried not to duplcate or follow Euilimchwalyo somehow.