• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.51-57
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• 2018

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• 한국소프트웨어감정평가학회 논문지
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• 제14권2호
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• pp.35-44
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• 2018

서로 다른 언어로 작성된 소스코드의 유사성 검사는 주로 요약구문트리를 기반으로 비교를 수행한다. 하지만 대규모의 소스코드를 실용적인 수준으로 비교하려면 토큰수준 기반에서 작동하는 유사성 검사 기술이 필요하다. 본 연구에서는 서로 다른 언어에서 생성되었지만 같은 의미를 지닌 토큰을 표현할 수 있는 공통 토큰을 정의하고, 소스코드에서 언어별 처리 과정을 거쳐 생성한 공통 토큰의 나열을 입력으로 소스코드의 유사성 검사를 수행하는 방법을 제안한다. 한국저작권위원회의 표절검사 도구 exEyes를 사용해서 서로 다른 언어로 작성된 동일한 코드를 대상으로 실험한 결과, 제안한 방법을 사용했을 때, 유사성 평가 성능이 향상됨을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.800-803
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• 2004

This paper presents a wavelet-based digital watermarking technique for still images. The digital watermarking considering human visual system (HVS) to increase the robustness and perceptual invisibility of digital watermark. The watermarking embedding is modified discrete wavelet transform (DWT) coefficients of the subbands of the images. The human visual system is number of factors that effect the noise sensitivity of human eyes that is considered to increase the robustness and perceptual invisibility of digital watermark. The watermark detection is blind watermark ( original image is not required ). Experimental results successful against attacks by image processing such as add noise, cropping, filtering, JPEG and JPEG2000 compression.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.249-252
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• 2005

본 논문에서는 자동차를 운전 시에 운전자의 얼굴과 눈의 영역을 자동으로 검출하고 눈동자를 추적하여 운전자의 졸음 여부를 판단하는 효과적인 시스템 구현방법을 제안한다. 복잡한 배경에서 얼굴과 눈을 검출하는 방법은 Haar-like feature의 원리를 이용하고 졸음운전으로 판단하는 방법은 눈동자 영역의 특성과 눈동자의 검출 유무, 움직임 등의 인식을 통하여 졸음운전 경보시스템의 실용화에 대한 가능성을 확인한다.

• 한국컴퓨터산업학회논문지
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• 제4권10호
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• pp.631-642
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• 2003

본 논문에서는 웹상에서 자신을 대신하는 아바타 제작시 본인의 얼굴과 닮은 얼굴을 생성하기 위해 사진으로부터 개인의 특징정보를 추출하는 방법과 추출된 특징정보에 따라 해당하는 이목구비를 준비된 분류기준에 의해 특정 클래스로 분류해 내는 방법을 제안한다. 특징정보 추출은 눈, 코, 입, 턱선으로 나누어 진행되어졌으며, 각 이목구비의 특징점과 분류기준을 각각 제시하였다. 추출 된 특징정보들은 전문 디자이너에 의해 그려진 이목구비 이미지들과 유사도를 계산하는데 사용되었으며, 여기서 가장 유사한 이미지를 턱선 벡터이미지에 합성하여 아바타 얼굴을 얻어낼 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제31권1호
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• pp.27-32
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• 2010

Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.102.3-102
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• 2001

In this paper, we propose a novel method that can detect face region effectively with fuzzy theory and neural network We make fuzzy rules and membership functions to describe the face color. In this algorithm, we use a perceptually uniform color space to increase the accuracy and stableness of the nonlinear color information. We use this model to extract the face candidate, and then scan it with the pre-built sliding window by using a neural network-based pattern-matching method to find eye. A neural network examines small windows of face candidate, and decides whether each window contains eye. We can standardize the face candidate geometrically with detected eyes.

• 제어로봇시스템학회논문지
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• 제9권12호
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• pp.984-993
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• 2003

In Gravure printing process, there are a lot of printing errors caused by expansion and contraction of printing materials and difficulty of printing of small letters, accordingly we cannot detect those errors with eyes. In this paper, we describe the algorithm which can detect small errors automatically in Gravure printing process and a real-time detection system adopting the algorithm. We present the Perimetric Mask algorithm that can eliminate tiny errors occurring near the contour of printing objects to achieve accurate inspection, and also construct an algorithm utilizing symmetry transform which can emphasize tiny errors to make a robust inspection system. We have made a system running in real-time and verified the efficiency of the algorithm.

• International Journal of Contents
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• 제8권1호
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• pp.16-22
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• 2012

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.