• Journal of KIISE
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• v.43 no.12
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• pp.1351-1355
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• 2016

The number of CCTV units is rapidly increasing annually, and the demand for intelligent video-analytics system is also increasing continuously for the effective monitoring of them. The existing analytics engines, however, require considerable computing resources and cannot provide a sufficient detection accuracy. For this paper, a light analytics engine was employed to analyze video and we collected metadata, such as an object's location and size, and the dwell time from the engine. A further data analysis was then performed to filter out the target of interest; as a result, it was possible to verify that a light engine and the heavy data analytics of the metadata from that engine can reject an enormous amount of environmental noise to extract the target of interest effectively. The result of this research is expected to contribute to the development of active intelligent-monitoring systems for the future.

• Journal of radiological science and technology
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• v.41 no.5
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• pp.391-396
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• 2018

The purpose of this study was to compare and analyze the patient dose according to the distance between the X-ray tube focus and the image receptor, and to propose a new method for quantitatively evaluating the image quality. Using this quantitative evaluation method, the optimal distance for increasing x-ray image quality with low radiation dose was estimated between source and image receptor in Rib series radiography. Phantom images were obtained by changing the distance between focus and image receptor (100 cm and 180 cm). The patient radiation dose was estimated using entrance surface dose and dose area product. In order to evaluate image quality objectively, a non - reference image evaluation method was employed with paper and salt noise and Gaussian filter. As a result of this study, when the SID was changed from 100 cm to 180 cm, the entrance surface dose decreased by 4 ~ 5 times and the dose area product decreased by 3 times. In addition, there is no significant difference in image quality between of SID 180 cm and SID 100 cm. In conclusion, it was demonstrated that performing the rib series radiography at SID 180 cm is an optimal method to reduce the exposure dose and improve the image quality.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.77-87
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• 2013

In this paper, we present a novel method for local image descriptor called exact order based descriptor (EOD) which is robust to illumination changes and Gaussian noise. Exact orders of image patch is induced by changing discrete intensity value into k-dimensional continuous vector to resolve the ambiguity of ordering for same intensity pixel value. EOD is generated from overall distribution of exact orders in the patch. The proposed local descriptor is compared with several state-of-the-art descriptors over a number of images. Experimental results show that the proposed method outperforms many state-of-the-art descriptors in the presence of illumination changes, blur and viewpoint change. Also, the proposed method can be used for many computer vision applications such as face recognition, texture recognition and image analysis.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.51-58
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• 2010

This work examines the identification of stiffness reduction in damaged reinforced concrete bridges under moving loads, and carries out the performance assessment after repairing using advanced composite materials. In particular, the change of stiffness in each element before and after repairing, based on the Microgenetic algorithm as an advanced inverse analysis, is described and discussed by using a modified bivariate Gaussian distribution function. The proposed method in the study is more feasible than the conventional element-based method from computation efficiency point of view. The validity of the technique is numerically verified using a set of dynamic data obtained from a simulation of the actual bridge modeled with a three-dimensional solid element. The numerical examples show that the proposed technique is a feasible and practical method which can inspect the complex distribution of deteriorated stiffness although there is a difference between actual bridge and numerical model as well as uncertain noise occurred in the measured data.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.756-763
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• 2013

Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.23-38
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• 2005

The state of channel between two or more wireless terminals is changed frequently due to noise or multiple environmental conditions in wireless network. In this paper, we analyze packet transmission time and queue length in a time-varying channel of packet based Wireless Networks. To reflect the feature of the time-varying channel, we model the channel as two-state Markov model and three-state Markov model Which are transformed to SFG(Signal Flow Graph) model, and then the distribution of the packet transmission can be modeled as Gaussian distribution. If the packet is arrived with Poisson distribution, then the packet transmission system is modeled as M/G/1. The average transmission time and the average queue length are analyzed in the time-varying channel, and are verified with some simulations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, the forensic marking algorithm is proposed using psychoacoustic model II and MDCT for high-quality audio. The proposed forensic marking method, that inserts the user fingerprinting code of the audio content into the selected sub-band, in which audio signal energy is lower than the spectrum masking level. In the range of the one frame which has 2,048 samples for FFT of original audio signal, the audio forensic marking is processed in 3 sub-bands. According to the average attack of the fingerprinting codes, one frame's SNR is measured on 100% trace ratio of the collusion codes. When the lower strength 0.1 of the inserted fingerprinting code, SNR is 38.44dB. And in case, the added strength 0.5 of white gaussian noise, SNR is 19.09dB. As a result, it confirms that the proposed audio forensic marking algorithm is maintained the marking robustness of the fingerprinting code and the audio high-quality.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.27-33
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• 2010

In this study, we conducted the classification experiments with GMM (Gaussian Mixture Model) from combining the extracted features by using microphone, Gyro sensor and Acceleration sensor in 9 different environment types. Existing studies of Context Aware wanted to recognize the Environment situation mainly using the Environment sound data with microphone, but there was limitation of reflecting recognition owing to structural characteristics of Environment sound which are composed of various noises combination. Hence we proposed the additional application methods which added Gyro sensor and Acceleration sensor data in order to reflect recognition agent's movement feature. According to the experimental results, the method combining Acceleration sensor data with the data of existing Environment sound feature improves the recognition performance by more than 5%, when compared with existing methods of getting only Environment sound feature data from the Microphone.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.863-870
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• 2009

Bilateral filter (BF) is a nonlinear filter for sharpness enhancement and noise removal. The BF performs the function by the two Gaussian filters, the domain filter and the range filter. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF with the adaptive standard deviation based on the analysis of the edge component of the local window, also having the variable filter size. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is robust and efficient than the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.