• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.445-452
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• 2010

In this paper, an attempt has been made to design the controller applicable for H.264 level3 encoder of baseline profile on full hardware basis. The designed controller module first stores the images supplied from CMOS Image Sensor(CIS) at main memory, and then reads or stores the image data in macroblock unit according to encoder operation. The timing cycle of the DMA controller required to process a macroblock is 478 cycles. In order to verify the our design, reference-C encoder, which is compatible to JM 9.4, is developed and the designed controller is verified by using the test vector generated from the reference C code. The number of cycle in the designed DMA controller is reduced by 40% compared with the cycle of using Xilinx MIG.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.949-952
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• 2009

In this paper, a watermarking method based on the trellis code with multi-layer is proposed. An image is divided $8{\times}8$ block with no overlapping, and compute the discrete cosine transform(DCT) of each block, and the 12 medium-frequency AC terms from each block are extracted. Next it is compared with gaussian random vectors with zero mean and unit variance. As these processing, the embedding vectors with minimum linear correlation can be obtained by Viterbi algorithm at each layer of trellis coding. To evaluate the performance of proposed method, the average bit error rate of watermark message is calculated from different several images.

• Annual Conference of KIPS
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• 2011.11a
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• pp.357-360
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• 2011

모자이크는 여러 개의 작은 영상들을 모아서 하나의 큰 영상을 만드는 것을 말한다. 본 논문에서는 모자이크 방법 중 하나인 사진을 이용하여 영상을 만드는 포토 모자이크 방법을 컴퓨터 알고리즘으로 구현하는 기술 제안을 한다. 이미지를 원하는 사이즈의 타일로 나눈 다음, 나눠진 타일을 16등분을 한다. 16등분된 이미지 각 요소들에 대하여 RGB 평균값을 계산하여 총 48개 특징값을 추출하여 데이터베이스에 저장해둔다. 그리고 타일과 비교가 될 이미지들은 이미 똑같은 작업을 통하여 데이터베이스에 저장이 되어 있다. 이렇게 저장된 값들을 통하여 유클리드 거리를 통하여 두 이미지의 유사도를 측정하게 된다. 최적의 값을 찾으면 바로 대입하는 것이 아니라 이전에 있던 타일 이미지의 명암값을 새로 삽입되는 타일에 부여를 하여, 부드러운 영상을 만들게 된다. 그리고 타일을 삽입할 때 이전에 사용된 이미지는 배열의 마지막으로 옮겨지게 되며 사용횟수를 체크하여 반복적 사용을 제한하였다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.93-101
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• 2009

This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.274-276
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• 2006

e-seal은 RFID(Radio Frequency IDentification) 기술을 사용하여 원격에서 자동으로 봉인상태를 확인할 수 있는 컨테이너 봉인 장치를 말한다. RFID의 특징상 반도체 칩에 기록된 정보를 제 삼자가 쉽게 판독 및 변조할 수 있다는 취약점으로 인하여 활성화되지 못하고 있는 실정이다. ISO에서는 RFID의 취약점을 보안하기 위한 표준작업(ISO 18185)을 진행 중이다. 이 중, ISO 18185-4는 e-seal에 저장되는 자료나 리더와의 RF통신에서 데이터 보호를 위한 표준이다. 이와 관련된 연구로는 인증 프로토콜과 ISO 18185-4를 위한 보고서로 제출된 보안 프로토콜이 있다. 제안된 e-seal 보안 프로토콜을 적용하기 위해서는 e-seal과 리더 간의 데이터를 암/복호화할 키가 필요하지만, 키 서버를 통해 전달받은 마스터 키를 데이터 암/복호화 키로 바로 사용하는 것은 보안 상의 문제점을 야기할 수 있기 때문에 PRF(Pseudo Random Function)을 이용하여 마스터 키로부터 MTK(Mutual Transient Key)를 유도하고, MTK를 암/복호화 키로 사용해야 한다. 기존의 PRF는 일방향 해시 함수(MD5, SHA 등)를 기반으로 하는 HMAC[2. 3]을 일반적으로 사용하였다. 그러나 일방향 해시 함수는 e-seal과 같은 제한된 자원을 갖는 환경에 적합하지 않다. 따라서, 본 논문에서는 e-seal 보안 프로토콜을 위한 효율적인 PRF을 제안한다. 기존의 일방향 해시 함수 기반이 아닌 블록 암호화 알고리즘을 기반으로 하는 MAC을 이용하여 PRF을 보다 효율적으로 구현하였고, 블록 암호화 알고리즘은 AES를 선택 합성체 $GF((2^4)^2)$을 통해 하드웨어 모듈을 최적화 하였다. AES를 기반으로 하는 MAC은 HMAC에 비해 면적 및 처리율에서 뛰어난 결과를 보여주었다.<0.01).이상의 연구 결과, cook-chill생산 시 녹차 추출물의 첨가가 미생물적 품질유지에 효과가 있다고 사료되는 바 본 연구결과를 기초로 급식소에서 음식 생산 시 녹차 추출물 및 천연 항균성 물질 첨가에 따른 미생물적 품질 및 관능적 품질검사를 통한 레시피 개발에 관한 지속적인 연구가 수행되어야 하겠다.다.다리다보니 점심시간을 활용할 수 없게 되는 문제점에 대한 재검토가 필요하다. 따라서 차후 학교급식의 안전성 확보를 위한 급식환경 개선의 일환으로 식당공간 확보 시 신속한 시간 내에 급식이 가능하도록 넓은 공간과 쾌적한 환경의 식당 조성에 대해 관심을 기울여야 할 것으로 사료된다. 이상 여부를 반영하는 임상증상의 빈도가 높은 청소년기 남녀 중학생의 경우 아침과 저녁의 결식빈도 및 외식과 간식의 빈도가 높았고, 아침식사의 질과 체형만족도가 낮은 것으로 나타나 청소년의 건강과 식습관 및 체형만족도가 상호 관련성이 높은 것으로 나타났다. 따라서 본 연구 결과는 성장기 청소년의 건강 유지를 위하여 바람직한 식습관의 중요성을 재인식할 수 있었으며, 올바른 식습관 확립을 위한 영양교육의 중요성이 재확인되었다.경제적일 것으로 판단된다.er 90 % of good relative dynamic modulus of elasticity due to fineness of formation caused by the increase of the unit powder content and the improvement of flowability, without regard to the replacement of crushed stone fines. Therefore, it can be said that the usage of crushed stone fines can control the strength of super flowing concrete by replacement and re

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.1-10
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• 2020

In this paper, we propose a new pornographic content detection scheme using bi-directional relationships between neighboring auditory signals in order to accurately detect sound-centered obscene contents that are rapidly spreading via the Internet. To capture the bi-directional relationships between neighboring signals, we design a multilayered bi-directional dilated-causal convolution network by stacking several dilated-causal convolution blocks each of which performs bi-directional dilated-causal convolution operations. To verify the performance of the proposed scheme, we compare its accuracy to those of the previous two schemes each of which uses simple auditory feature vectors with a support vector machine and uses only the forward relationships in audio signals by a previous stack of dilated-causal convolution layers. As the results, the proposed scheme produces an accuracy of up to 84.38% that is superior performance up to 25.80% than other two comparison schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1703-1710
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• 2017

This paper propose a 3D point clouds (depth) security technique for digital holographic display service. Image contents encryption is a method to provide only authorized right owners with the original image information by encrypting the entire image or a part of the image. The proposed method detected an edge from a depth and performed quad tree decomposition, and then performed encryption. And encrypts the most significant block among the divided blocks. The encryption effect was evaluated numerically and visually. The experimental results showed that encrypting only 0.43% of the entire data was enough to hide the constants of the original depth. By analyzing the encryption amount and the visual characteristics, we verified a relationship between the threshold for detecting an edge-map. As the threshold for detecting an edge increased, the encryption ratio decreased with respect to the encryption amount.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.463-470
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• 2009

In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.234-240
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• 2022

This paper proposes a customized AI exercise recommendation service for balancing the relative amount of exercise according to the working environment by each occupation. WISDM database is collected by using acceleration and gyro sensors, and is a dataset that classifies physical activities into 18 categories. Our system recommends a adaptive exercise using the analyzed activity type after classifying 18 physical activities into 3 physical activities types such as whole body, upper body and lower body. 1 Dimensional convolutional neural network is used for classifying a physical activity in this paper. Proposed model is composed of a convolution blocks in which 1D convolution layers with a various sized kernel are connected in parallel. Convolution blocks can extract a detailed local features of input pattern effectively that can be extracted from deep neural network models, as applying multi 1D convolution layers to input pattern. To evaluate performance of the proposed neural network model, as a result of comparing the previous recurrent neural network, our method showed a remarkable 98.4% accuracy.