• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.453-456
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• 2005

일반적으로 심전도는 심장계통의 질환을 판단할 때 사용된다. 이러한 심장질환의 이상 유무를 자동으로 진단하기 위해서는 QRS파형 검출을 필요로 하며, 이를 위하여 웨이블렛변환 방법이나 템플릿매칭, 룰 베이스 방법 등 여러 가지 방법들이 쓰이고 있으나, 심전도 신호가 표준화된 형태를 갖지 않는 경우는 검출 능력에 많은 한계를 갖고 있다. 본 논문은 파형의 베이스라인(baseline)을 기준으로 진폭 값에 절대치을 취하는 방법으로 파형의 R피크값을 검출하는 알고리즘을 제안한다. 결과를 검증하기 위해 MIT-BIH 데이타베이스에서 제공하는 데이터와 R피크값을 본 논문의 알고리즘으로 추출된 R피크값과 비교한 결과 96.7%의 검출률을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1025-1030
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• 2005

With the increasing use of multimedia technologies, image compression requires higher performance as well as new functionality. Specially, in the specific area of still image encoding, a new standard, JPEG2000 was developed. This paper proposed Set Partitioning Sorting Algorithm that uses a method to optimized selection of threshold from feature of wavelet transform coefficients and to removes sign bit in LL area on JPEG2000. Experimental results show the proposed algorithm achieves more improved bit rate.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.357-357
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• 2021

홍수로 인한 침수피해 발생을 최소화하기 위해 정확한 하천의 수위 예측과 리드타임 확보가 매우 중요하다. 특히 조석현상의 영향을 받는 감조하천의 경우 기존의 물리적 수문모형의 적용이 제한되어 하천수위 예측의 정확도가 떨어지기도 한다. 따라서 본 연구에서는 이러한 감조하천 수위 예측의 정확도를 높이기 위해 조석현상을 분리하고 인공신경망을 활용하는 하이브리드 모델을 제안 하였으며 다중 선형회귀분석과 비교 분석하였다. 감조하천에 위치한 교량의 수위데이터에서 Stationary Wavelet Transform으로 조석현상을 분리하였으며, 이외의 수위에 영향을 주는 time series data와 인공신경망(ANN)을 활용하여 1시간, 2시간, 3시간 후의 수위를 예측하였다. 하이브리드 모델은 96% 이상의 정확도를 보였으며 다중 선형회귀 분석과 비교하여도 높은 정확성을 보여주었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.12
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• pp.18-25
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• 2005

This paper presents a supercompact multi-wavelet scheme and its application to fluid simulation data. The supercompact wavelet method is an appropriate wavelet for fluid simulation data in the sense that it can provide compact support and avoid unnecessary interaction with remotely located data (e.g. across a shock discontinuity or vortices). thresholding for data compression is applied based on a covariance vector structure of multi-wavelets. The extension of this scheme to three dimensions is analyzed. The numerical tests demonstrate that it can allow various analytic advantages as well as large data compression ratios in actual practice.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.76-84
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• 1999

EZW proposed by Shapiro is based on a zerotree constructed in a way that a parent coefficient in a subband is related to four child coefficients in the next finer subband of similar orientation. This fixed treeing based on 1-to-4 parent-child is suitable to exploti hierachical correlations among subbands but not to exploit spatial correlations within a subband. A new treeing by Joo, et al. is suggested to simulatneously exploit those two correlatins by extending parent-child relationship in a flexible way. The flexible treeing leads to increasing the number of symbols and lowering entorpy comparing to the fixed treeing, and therefore a better compression can be resulted. In this paper, we suggest two techniques to suppress the increasing of symbols. First, a probing bit is generated to avoid redundant scan for insignivicant coefficients. Second, since all subbands do not always require the same kind of symbol-set, produced symbols are re-symbolized into binary codes according to a pre-defined procedure. Owing to those techniques, all symbols are generated as binary codes. The binary symbols can be entropy-coded by an adaptive arithmetic coding. Moerover, the binary symbol stream can give comparatively good performances without help of additional entropy coding. Our proposed coding scheme is suggested in two modes: binary coding mode and arithmetic coding mode. We evaluate the effectivenessof our modifications by comparing with the original EZW.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.91-98
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• 2009

This paper presents a solution to error avalanche of deciphering where radio noise brings random bit errors in encrypted image data under ubiquitous environment. The image capturing module is to be made comprising data compression and encryption features to reduce data traffic volume and to protect privacy. Block cipher algorithms may experience error avalanche: multiple pixel defects due to single bit error in an encrypted message. The new fault tolerant scheme addresses error avalanche effect exploiting a three-dimensional data shuffling process, which disperses error bits on many frames resulting in sparsely isolated errors. Averaging or majority voting with neighboring pixels can tolerate prominent pixel defects without increase in data volume due to error correction. This scheme has 33% lower data traffic load with respect to the conventional Hamming code based approach.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.48-57
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• 2007

Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported thus far still need to be improved about precision and computational time for successful applications. In this paper, we propose an improved eye localization method based on multi-scale Gator feature vector models. The proposed method first tries to locate eyes in the downscaled face image by utilizing Gabor Jet similarity between Gabor feature vector at an initial eye coordinates and the eye model bunch of the corresponding scale. The proposed method finally locates eyes in the original input face image after it processes in the same way recursively in each scaled face image by using the eye coordinates localized in the downscaled image as initial eye coordinates. Experiments verify that our proposed method improves the precision rate without causing much computational overhead compared with other eye localization methods reported in the previous researches.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.993-1000
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• 2012

In this research, we proposed an efficient VLSI architecture of the lifting-based 2D DWT (Discrete Wavelet Transform) filter with 100% hardware utilization. The (9,7) filter structure has been applied and extendable to the filter length. We proposed a new block-based scheduling that computes the DWT for the lower levels on an "as-early-as-possible" basis, which means that the calculation for the lower level will start as soon as the data is ready. Since the proposed 2D DWT computes the outputs of all levels by one row-based scan, the intermediate results for other resolution levels should be kept in storage such as the Data Format Converter (DFC) and the Delay Control Unit (DCU) until they are used. When the size of input image is $N{\times}N$ and m is the filter length, the required storage for the proposed architecture is about 2mN. Since the proposed architecture processes the 2D DWT in horizontal and vertical directions at the same time with 4 input data, the total period for 2D DWT is $N^2(1-2^{-2J})/3$.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.431-437
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• 2004

This paper propose a facial recognition method based on an ubiquitous computing that is one of next generation intelligence technology fields. The facial images are acquired by a mobile device so-called cellular phone camera. We consider a mobile security using facial feature extraction and recognition process. Facial recognition is performed by the PCA and fuzzy LDA algorithm. Applying the discrete wavelet based on multi-resolution analysis, we compress the image data for mobile system environment. Euclidean metric is applied to measure the similarity among acquired features and then obtain the recognition rate. Finally we use the mobile equipment to show the efficiency of method. From various experiments, we find that our proposed method shows better results, even though the resolution of mobile camera is lower than conventional camera.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.649-654
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• 2005

In this paper, we describe an implementation of real-time face recognition system under ubiquitous computing environments. First, face image is captured by PDA with CMOS camera and then this image with user n and name is transmitted via WLAN(Wireless LAN) to the server and finally PDA receives verification result from the server The proposed system consists of server and client parts. Server uses PCA and LDA algorithm which calculates eigenvector and eigenvalue matrices using the face images from the PDA at enrollment process. And then, it sends recognition result using Euclidean distance at verification process. Here, captured image is first compressed by the wave- let transform and sent as JPG format for real-time processing. Implemented system makes an improvement of the speed and performance by comparing Euclidean distance with previously calculated eigenvector and eignevalue matrices in the learning process.