• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.61-69
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• 2015

This study presents a probabilistic knowledge discovery method to interpret heart rate variability (HRV) based on time and frequency domain indexes, extracted using discrete wavelet transform. The knowledge induction algorithm was composed of two phases: rule generation and rule estimation. Firstly, a rule generation converts numerical attributes to intervals using ROC curve analysis and constructs a reduced ruleset by comparing consistency degree between attribute-value pairs with different decision values. Then, we estimated three measures such as rule support, confidence, and coverage to a probabilistic interpretation for each rule. To show the effectiveness of proposed model, we evaluated the statistical discriminant power of five rules (3 for atrial fibrillation, 1 for normal sinus rhythm, and 1 for both atrial fibrillation and normal sinus rhythm) generated using a data (n=58) collected from 1 channel wireless holter electrocardiogram (ECG), i.e., HeartCall$^{(R)}$, U-Heart Inc. The experimental result showed the performance of approximately 0.93 (93%) in terms of accuracy, sensitivity, specificity, and AUC measures, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1053-1059
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• 2005

The computer generated hologram (CGH) designs and produces digital information for generating 3-D (3-Dimension) image using computer and software instead of optically-sensed hologram of light interference, and it can synthesis a virtual object which is physically not in existence. Since digital hologram includes an amount of data as can be seen at the process of digitization, it is necessary that the data representing digital hologram is reduced for storing, transmission, and processing. As the efforts that are to handle hologram with a type of digital information have been increased, various methods to compress digital hologram called by fringe pattern are groped. Suitable proposal is encoding of hologram. In this paper, we analyzed the properties of CGH using tools of frequency transform, assuming that a generated CGH is a 2D image by introducing DWT that is known as the better tool than DCT for frequency transform. The compression and reconstruction result which was extracted from the wavelet-based codecs illustrates that it has better properties for reconstruction at the maximum 2 times higher compression rate than the Previous researches of Yoshikawa[2] and Thomas[3].

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.23-30
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• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.36-42
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• 2006

A Principal component analysis (PCA)-based Mel-Frequency Discrete Wavelet Coefficients (MFDWC) feature Parameters for speaker verification system is Presented in this Paper In this method, we used the 1st-eigenvector obtained from PCA to calculate the energy of each node of level that was approximated by. met-scale. This eigenvector satisfies the constraint of general weighting function that the squared sum of each component of weighting function is unity and is considered to represent speaker's characteristic closely because the 1st-eigenvector of each speaker is fairly different from the others. For verification. we used Universal Background Model (UBM) approach that compares claimed speaker s model with UBM on frame-level. We performed experiments to test the effectiveness of PCA-based parameter and found that our Proposed Parameters could obtain improved average Performance of $0.80\%$compared to MFCC. $5.14\%$ to LPCC and 6.69 to existing MFDWC.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.185-189
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• 2009

무선 센서 네트워크는 화산 감시, 전장 감시, 동물 서식지 감시, 건축물의 감시, 농장 관리, 의료분야등 다양한 분야에서 연구되고 있다. 국내에서도 국가 정책 사업으로 교량 및 건축물의 균열 감시, 표적의 침입 탐지 및 식별을 위한 무선 센서 네트워크 연구가 활발히 진행 중이다. 특히, 무선 센서 네트워크의 다양한 분야의 연구 중에서 철조망을 이용한 표적의 침입 탐지 및 식별에 관한 연구는 산업 시설, 보안지역, 교도소, 군사지역, 공항 등 다양한 분야에서 사용된다. 현재 철조망 감시는 대부분 유선 센서 노드를 통한 유선 센서 네트워크 환경에서 이루어지고 있다. 기존의 유선 센서 네트워크는 높은 데이터 전송률을 통해 수신되는 높은 정보의 신호를 이용하여 고속 푸리에 변환에 의한 신호의 주파수 분석 기법을 사용해 왔다. 하지만, 유선 센서 네트워크의 높은 데이터 전송률과 비교하여 무선 센서 네트워크의 센서 노드는 유선 센서 네트워크에 비해 매우 낮은 데이터 전송률을 가진다. 따라서 무선 센서 네트워크에서 수신되는 신호의 정보가 매우 낮고, 유선 센서 네트워크에서 사용된 고속 푸리에 변환에 의한 신호의 주파수 분석에 따른 주파수별 특징 추출을 할 수 없다. 따라서 본 논문에서는 철조망 감시를 위한 높은 데이터 전송률을 보장하는 유선 센서 네트워크에 비해 제한된 통신자원과 센서 노드의 낮은 데이터 전송률로 인해 수신되는 한정적인 신호의 정보를 이용한 무선 센서 네트 워크에서 철조망의 표적 침입 탐지 및 식별을 위한 특징 추출 알고리즘을 제안한다.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.89-94
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• 2013

This paper presents color video flame detection algorithm based on wavelet transform to remove detection of flickering non-flame objects. Conventional flame detection algorithms consist of simple or mixed functions using colors, temporal and spatial characteristics. But those algorithms detect non-flame objects as flame regions sometimes. False alarm reasons are flame-like objects with regular flickering lights such as car signal lamps, alarm lights etc. The proposed algorithm is to reduce false detection which is occurred in periodic flickering lights. At first, It segments the candidate flame regions by using frame difference, flame colors. Then it distinguish flame regions and non flame regions including flickering car lights by analyzing wavelet coefficients. Computer simulation results showed that the proposed algorithm removes false detection due to the periodic flickering lamps by performing 97.9% of correct detection rate while false detection rate is 7.3%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.1-12
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• 2013

Road's accidents caused by Ice, snow, Wet of roads surface conditions and weather conditions situations that are constantly occurring. That is, driver's negligence and safe driving ability of individuals due to lack of awareness, and Road management main agent(the government and the public, etc.) due to road conditions, if there is insufficient information. So Related research needs is a trend that is required. In this study, gather Camera(Stereo camera)'s image data, and analysis polarization coefficients and wavelet transform. And unlike traditional single-dimensional classification algorithms as multi-dimensional analysis by using SVM classification techniques, develop an algorithm to determine road conditions. Four on the road conditions (dry, wet, snow, ice) recognition success rate for the detection and analysis of experiments.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.847-858
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• 2012

In this paper, we propose a mobile watermarking based on the distortion analysis of display-capture image in a smart phone. We compose a random sequence by utilizing the property of frequency band in the wavelet domain. Then we calculate the CCS (Coefficients Comparative Sum) using the block wavelet coefficients of selected subbands after the wavelet transformation and the random sequence and repeatedly embed a watermark using an insertion threshold for the watermark robustness. For correcting a distortion caused by the display-capture process, we adopt a frame at the outside of watermarked image, then we can equate a watermark synchronization by detecting the frame. And we can improve frame detection ratio by using an iteratively adaptive threshold. A proposed scheme embedded information of 206 bits into standard digital images and it shows an average about 41.42 dB in PSNR. In watermark extract experiments, a proposed scheme accurately recognizes the frame more than 97% in total captured images. Also in BER (Bit Error Ratio) of captured images, it shows about 3.73%, then it was improved more than 70%, compared with the Pramila's method.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.936-941
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• 2006

To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.