• JSTS:Journal of Semiconductor Technology and Science
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• 제12권4호
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• pp.418-425
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• 2012

In this paper, efficient implementation of error correction code (ECC) processing circuits based on single error correction and double error detection (SEC-DED) code with check bit pre-computation is proposed for memories. During the write operation of memory, check bit pre-computation eliminates the overall bits computation required to detect a double error, thereby reducing the complexity of the ECC processing circuits. In order to implement the ECC processing circuits using the check bit pre-computation more efficiently, the proper SEC-DED codes are proposed. The H-matrix of the proposed SEC-DED code is the same as that of the odd-weight-column code during the write operation and is designed by replacing 0's with 1's at the last row of the H-matrix of the odd-weight-column code during the read operation. When compared with a conventional implementation utilizing the odd-weight- column code, the implementation based on the proposed SEC-DED code with check bit pre-computation achieves reductions in the number of gates, latency, and power consumption of the ECC processing circuits by up to 9.3%, 18.4%, and 14.1% for 64 data bits in a word.

• 한국멀티미디어학회논문지
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• 제19권11호
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• pp.1837-1851
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• 2016

Newspaper reader mobile applications using text-to-speech (TTS) function enable blind people to read newspaper contents. But, tables cannot be easily read by the reader program because most of the tables are stored as images in the contents. Even though we try to use OCR (Optical character reader) programs to recognize letters from the table images, it cannot be simply applied to the table reading function because the table structure is unknown to the readers. Therefore, identification of exact location of each table cell that contains the text of the table is required beforehand. In this paper, we propose an efficient image processing algorithm to recognize all the cells in tables by identifying columns and rows in table images. From the cell location data provided by the table column and row identification algorithm, we can generate table structure information and table reading scenarios. Our experimental results with table images found commonly in newspapers show that our cell identification approach has 100% accuracy for simple black and white table images and about 99.7% accuracy for colored and complicated tables.

• 전기학회논문지
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• 제63권12호
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• pp.1667-1670
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• 2014

This paper describes a method for detecting the pupil region and identification of the eye status for driver drowsiness detection system. This program detects a driver's face and eyes using viola-jones face detection algorithm and extracts the pupil area by utilizing mean values of each row and column on the eye area. The proposed method uses binary images and the number of black pixels to identify the eye status. Experimental results showed that the accuracy of classification eye status(open/close) was above 90%.

• 대한의용생체공학회:의공학회지
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• 제11권2호
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• pp.217-226
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• 1990

This paper presents a new algorithm that extracted lung region in X-ray and enhanced the region. With a lung region that was extracted by histogram threshold value, it was diffi cult to detect perfect lung boundary. Therefore we presented perfect lung boundary detection method using apex detection and apex region restoration. Also, by applying modified equalization algorithm and presented function to inside of lung region, we want to give help to automatic diagnosis In X-ray chest image. Presented main line trace algorithm gave good result in detection of lung boundary And, as apex detection method using lung row and column gray level average value found more correct place of lung than the rpethod of prior algorithm, we succeeded perfect lung region detection, Also, presented function that had lung region's gray level distribution characteristic was very effective to image enhancement.

• Bulletin of the Korean Chemical Society
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• 제29권6호
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• pp.1173-1178
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• 2008

A simple and sensitive high-performance liquid chromatographic method was developed for the simultaneous identification of enrofloxacin and its active metabolite ciprofloxacin in chicken muscle. Norflorxacin imprinted polymers synthesized in water-containing systems show high selectivity to enrofloxacin and ciprofloxacin in an aqueous environment. Using these water-compatible imprinted polymers as selective adsorbents in the solid-phase extraction of enrofloxacin and ciprofloxacin from chicken samples, the remaining biological matrix could be quickly washed out from the imprinted column while enrofloxacin and ciprofloxacin were selectively retained and enriched. Analytical separation was performed on a $C_{18}$ column using acetonitrile-water as a mobile phase and fluorescence detection. Good linearity was obtained from 0.8 to 500 ng/g (r > 0.998) with relative standard deviation of less than 3.9%. The mean recoveries of enrofloxacin and ciprofloxacin from chicken muscle were 80.6-94.5% and 77.8-91.8% at three different concentrations. The limits of determinations based on S/N=3 were 0.07 ng/g and 0.09 ng/g, which are below the maximum residue limits established in many countries.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.195-201
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• 2015

For median filtering (MF) detection in altered digital images, this paper presents a new feature vector that is formed from autoregressive (AR) coefficients via an AR model of the gradients between the neighboring row and column lines in an image. Subsequently, the defined 10-D feature vector is trained in a support vector machine (SVM) for MF detection among forged images. The MF classification is compared to the median filter residual (MFR) scheme that had the same 10-D feature vector. In the experiment, three kinds of test items are area under receiver operating characteristic (ROC) curve (AUC), classification ratio, and minimal average decision error. The performance is excellent for unaltered (ORI) or once-altered images, such as $3{\times}3$ average filtering (AVE3), QF=90 JPEG (JPG90), 90% down, and 110% up to scale (DN0.9 and Up1.1) images, versus $3{\times}3$ and $5{\times}5$ median filtering (MF3 and MF5, respectively) and MF3 and MF5 composite images (MF35). When the forged image was post-altered with AVE3, DN0.9, UP1.1 and JPG70 after MF3, MF5 and MF35, the performance of the proposed scheme is lower than the MFR scheme. In particular, the feature vector in this paper has a superior classification ratio compared to AVE3. However, in the measured performances with unaltered, once-altered and post-altered images versus MF3, MF5 and MF35, the resultant AUC by 'sensitivity' (TP: true positive rate) and '1-specificity' (FN: false negative rate) is achieved closer to 1. Thus, it is confirmed that the grade evaluation of the proposed scheme can be rated as 'Excellent (A)'.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.558-575
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• 2013

The purpose of a data leakage prevention system is to protect corporate information assets. The system monitors the packet exchanges between internal systems and the Internet, filters packets according to the data security policy defined by each company, or discretionarily deletes important data included in packets in order to prevent leakage of corporate information. However, the problem arises that the system may monitor employees' personal information, thus allowing their privacy to be violated. Therefore, it is necessary to find not only a solution for detecting leakage of significant information, but also a way to minimize the leakage of internal users' personal information. In this paper, we propose two models for representing the level of personal information disclosure during data leakage detection. One model measures only the disclosure frequencies of keywords that are defined as personal data. These frequencies are used to indicate the privacy violation level. The other model represents the context of privacy violation using a private data matrix. Each row of the matrix represents the disclosure counts for personal data keywords in a given time period, and each column represents the disclosure count of a certain keyword during the entire observation interval. Using the suggested matrix model, we can represent an abstracted context of the privacy violation situation. Experiments on the privacy violation situation to demonstrate the usability of the suggested models are also presented.

• 한국산업정보학회논문지
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• 제28권2호
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• pp.11-19
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• 2023

본 논문은 인보이스 문서 이미지에 문서 처리 자동화를 적용하기 위한 문서 구조 인식 방법과 문서 구조 인식 결과를 토대로 스프레드문서 형태로 출력하는 방법을 제안한다. 딥러닝 OCR 엔진을 통해 문서 내 단어 블록들과 해당 블록들의 문자 인식 결과를 얻는다. 단어 블록의 위치 정보들을 통해 같은 행과 같은 열에 존재하는 단어 블록들을 검출한다. 단어 블록들의 배치 정보를 통해 문서 영역을 분할한다. 문서의 구역 정보를 통해 얻어진 문서 구조를 토대로 스프레드시트의 알맞은 위치에 문자 인식 결과를 입력한다. 실험 결과 제안된 방법을 통한 항목 배치는 평균 92.30%의 정확도를 보인다.

• 전자공학회논문지
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• 제52권8호
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• pp.67-73
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• 2015

디지털 영상의 배포에서, 위 변조자에 의해 영상이 변조되는 심각한 문제가 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 영상의 Fourier 변환 변이계수를 이용한 미디언 필터링 (Median Filtering: MF) 영상의 포렌식 판정 알고리즘을 제안한다. 제안된 알고리즘에서, 영상의 각 수평, 수직라인의 Fourier 변환 (Fourier Transform: FT)을 하고, 이웃 라인과의 변이계수를 기반으로 하여 MF 검출 (Median Filtering Detection: MFD)을 위한 10 Dim. 특징벡터를 정의한다. 이는 MF 검출기의 SVM (Support Vector Machine) 학습에 사용된다. 제안된 미디언 필터링 검출 스킴은 동일 10 Dim. 특징벡터의 MFR (Median Filter Residual)과 Rhee의 MF 검출 스킴과 비교하여 원영상, JPEG (QF=90), Down 스케일링 (0.9) 그리고 Up 스케일링 (1.1) 영상에서는 성능이 우수하며, Gaussian 필터링($3{\times}3$) 영상에서는 성능이 일부 높았다. 제안된 알고리즘은 성능평가 전체항목에서 민감도 (Sensitivity; TP: True Positive rate)와 1-특이도 (1-Specificity; FP: False Positive rate)에 의한 AUC (Area Under ROC (Receiver Operating Characteristic) Curve)가 모두 1에 수렴하여 'Excellent (A)' 등급임을 확인하였다.

• 전자공학회논문지SC
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• 제47권6호
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• pp.86-96
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• 2010

본 논문에서는 U-시차맵과 조감도를 이용한 스테레오 비전 기반의 장애물체 검출 및 차량 검증 방법을 제안한다. 먼저 최대 빈도 값을 이용하여 V-시차맵 상에서 도로 특징 정보를 추출하고, 추출된 도로 정보를 이용하여 대략적인 도로상의 장애물체 영역을 추출한다. 좀 더 정확한 장애물체 영역 추출을 위하여 U-시차맵을 생성하는데, 이때 시차값과 카메라 파라미터를 이용하여 계산된 문턱치를 이용하여 높이 제한된 U-시차맵을 생성함으로써, 일정한 높이의 장애물체만을 검출 할 수 있다. 그러나 검출된 장애물체 영역 내에는 여전히 다수의 장애물체와 배경이 존재하므로, 세그먼테이션 과정을 수행한다. 전 단계에서 추출된 장애물체 영역을 카메라 모델링과 파라미터를 이용하여 조감도 맵핑을 수행한다. 조감도는 시차맵과 카메라 정보를 기반으로 계산된 장애물체들의 위치를 평면상에 표시함으로써 장애물체들을 좀 더 쉽게 분리할 수 있다. 마지막으로 각각 분리된 장애물체들 별로 차량 특징 기반의 차량 검증 과정을 수행한다. 도로 접점 여부, 일정한 수평크기, 가로 세로 비율 및 텍스쳐 정보를 이용하여 최종적으로 도로상의 차량만을 검출한다. 그리고 실제 도로에서 획득한 영상에 제안한 알고리즘을 적용함으로써 장애물체 검출 및 차량 검증 성능을 검증한다.