• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.39-46
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• 2009

Many lip region detection methods have been developed in PC environment. But the existing methods are difficult to run on real-time in resource limited mobile devices. To solve the problem, this paper proposes a real-time lip region detection method for lipreading in Mobile device. It detects face region by using adaptive face color information. After that, it detects lip region by using geometrical relation between eyes and lips. The proposed method is implemented in a smart phone with Intel PXA 270 embedded processor and 386MB memory. Experimental results show that the proposed method runs at the speed 9.5 frame/see and the correct detection rate was 98.8% for 574 images.

• Journal of Astronomy and Space Sciences
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• v.17 no.1
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• pp.53-66
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• 2000

We developed low light CCD imaging system using thermoelectric cooling method collaboration with a company to design a commercial model. It consists of Kodak KAF-0401E(768$\times$512 pixels) CCD chip, thermoelectric module manufactured by Thermotek. This TEC system can reach an operative temperature of $-25^{\circ}C$. We employed an Uniblitz VS25s shutter and it has capability a minimum exposure time 80ms. The system components are an interface card using a Korea Astronomy Observatory (hereafter KAO) ISA bus controller, image acquisition with AD9816 chip, that is 12bit video processor. The performance test with this imaging system showed good operation within the initial specification of our design. It shows a dark current less than 0.4e-/pixel/sec at a temperature of $-10^{\circ}C$, a linearity 99.9$\pm$0.1%, gain 4.24e-/adu, and system noise is 25.3e-(rms). For low temperature CCD operation, we designed a TEC, which uses a one-stage peltier module and forced air heat exchanger. This TEC imaging system enables accurate photometry($\pm$0.01mag) even though the CCD is not at 'conventional' cryogenic temperatures(140k). The system can be a useful instrument for any other imaging applications. Finally, with this system, we obtained several images of astronomical objects for system performance tests.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.11
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• pp.43-53
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• 2010

Wide deployment of high resolution video services leads to active studies on high speed video processing. Especially, prevalent employment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. In this paper, we propose a novel parallel H.264/AVC decoding scheme on a multi-core platform. Parallel H.264/AVC decoding is challenging not only because parallelization may incur significant synchronization overhead but also because software may have complicated dependencies. To overcome such issues, we propose a novel approach called Multi-Threaded Parallelization(MTP). In MTP, to reduce synchronization overhead, a separate thread is allocated to each stage in the pipeline. In addition, an efficient memory reuse technique is used to reduce the memory requirement. To verify the effectiveness of the proposed approach, we parallelized FFmpeg H.264/AVC decoder with the proposed technique using OpenMP, and carried out experiments on an Intel Quad-Core platform. The proposed design performs better than FFmpeg H.264/AVC decoder before the parallelization by 53%. We also reduced the amount of memory usage by 65% and 81% for a high-definition(HD) and a full high-definition(FHD) video, respectively compared with that of popular existing method called 2Dwave.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.149-156
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• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.158-158
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• 2017

비닐포장 하부에 위치한 콩의 생장 초기에 발생한 초엽을 인식하기 위한 연구를 수행중이다. 선행 연구에서 비닐포장에 접촉한 콩 초엽으로 인해 비닐포장 상부 표면의 열 반응 분포에 변화가 있음을 발견하였다. 현장에서 주행 중에 콩 초엽의 위치를 실시간으로 인식하고 연동된 선형 또는 회전형 엑츄에이터를 제어하여 정확한 위치에 천공을 수행하기 위해서는 계측 시스템과 제어 시스템간의 시간적 차이를 최소할 수 있는 실시간 신호 처리 기술이 필수적이다. 선행 연구에서 사용한 다중 IR 센서의 분해능은 $16{\times}4pixel$이며 주파수는 3 Hz로, 폭이 30cm 내외인 비닐포장 상부의 정밀 분석에 한계가 있음을 발견하였다. 이를 해결하기 위하여 분해능과 계측 주기를 개선할 수 있는 초소형 ($1cm{\times}1cm{\times}1cm$) 열화상 센서를 이용하였다. LWIR(Longwave infrared)영역에 해당하는 $8{\mu}m{\sim}14{\mu}m$의 영역에서 $0.05^{\circ}C$의 분해능을 보이는 $ Lepton^{TM}$ (500-0690-00, FLIR, Goleta, CA)모델을 사용하였다. 프레임당 $80{\times}60$ 픽셀의 정보가 2 Byte의 단위로 계측이 되며 9 Hz의 주파수로 대상면의 열 분포를 측정할 수 있다. 이론적으로 초당 정보 전송량은 86,400 Byte ($80{\times}60{\times}2{\times}9$)이며, 1 m를 진행하는 주행형 천공기에 적용할 경우 1 프레임당 10cm 정도의 면적을 측정하므로, 최대 위치 판정 분해능은 약 10 cm / 60 pixel = 0.17 cm/pixel로 상대적으로 정밀한 위치 판별이 가능하다. $80{\times}60{\times}2Byet$의 정보를 0.1초 이내에 분석해야 하는 기술적 과제를 해결하기 위하여 천공 작업기에 적합한 상용 SBC(Single board computer)의 클럭 속도(1 Ghz)로 처리 가능한 공간 분포 분석 알고리즘을 개발하였다. 전체 이미지 도메인을 한 번에 분석하는데 소요되는 시간을 최소화하기 위하여 공간정보 행렬을 균등히 배분하고 별도의 프로세서에서 Feature를 분석한 후 개별 프로세서의 결과를 경합식으로 판정하는 기술을 연구하였다. 오픈 소스인 MPICH(www.mpich.org) 라이브러리를 이용하여 개발한 신호 분석 프로그램을 클러스터링으로 연동된 개별 코어에 설치/수행 하였다. 2D 행렬인 열분포 정보를 공간적으로 균등 분배하여 개별 코어에서 행렬의 Spatial domain analysis를 수행하였다. $20{\times}20$의 클러스터링 단위를 이용할 경우 총 12개의 코어가 필요하였으며, 초당 10회의 연산이 가능함을 확인하였다. 병렬 클러스터링 기술을 이용하여 1m/s 내외의 주행 속도에 대응이 가능한 비닐포장 상부 열 분포 분석 시스템을 구현하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.35-41
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• 2020

Fast Fourier transform (FFT) processors have been widely used in various application such as communications, image, and biomedical signal processing. Especially, high-performance and low-power FFT processing is indispensable in OFDM-based communication systems. This paper presents a novel radix-26 FFT algorithm with low computational complexity and high hardware efficiency. Applying a 7-dimensional index mapping, the twiddle factor is decomposed and then radix-26 FFT algorithm is derived. The proposed algorithm has a simple twiddle factor sequence and a small number of complex multiplications, which can reduce the memory size for storing the twiddle factor. When the coefficient of twiddle factor is small, complex constant multipliers can be used efficiently instead of complex multipliers. Complex constant multipliers can be designed more efficiently using canonic signed digit (CSD) and common subexpression elimination (CSE) algorithm. An efficient complex constant multiplier design method for the twiddle factor multiplication used in the proposed radix-26 algorithm is proposed applying CSD and CSE algorithm. To evaluate performance of the previous and the proposed methods, 256-point single-path delay feedback (SDF) FFT is designed and synthesized into FPGA. The proposed algorithm uses about 10% less hardware than the previous algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.68-74
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• 2009

In this paper, we propose an effective memory reduction algorithm to reduce the amount of reference frame buffer and memory bandwidth in video encoder and decoder. In general video codecs, decoded previous frames should be stored and referred to reduce temporal redundancy. Recently, reference frames are recompressed for memory efficiency and bandwidth reduction between a main processor and external memory. However, these algorithms could hurt coding efficiency. Several algorithms have been proposed to reduce the amount of reference memory with minimum quality degradation. They still suffer from quality degradation with fixed-bit allocation. In this paper, we propose an adaptive block-based min-max quantization that considers local characteristics of image. In the proposed algorithm, basic process unit is $8{\times}8$ for memory alignment and apply an adaptive quantization to each $4{\times}4$ block for minimizing quality degradation. We found that the proposed algorithm can obtain around 1.7% BD-bitrate gain and 0.03dB BD-PSNR gain, compared with the conventional fixed-bit min-max algorithm with 37.5% memory saving.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.26-32
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• 2008

Video compression schemes have been developed and used for many years. Currently, H.264/AVC is the most efficient video coding standard. The H.264/AVC baseline profile adopts CAVLC(Context-Adaptive Variable Length Coding) method as an entropy coding method. CAVLC gives better performance in compression ratios than conventional VLC(Variable Length Coding). However, because CAVLC decoder uses a lot of VLC tables, the CAVLC decoder requires a lot of area in terms of hardware. Conversely, since it must look up the VLC tables, it gives a worse performance in terms of software. In this paper, we propose a new hierarchical grouping method for the VLC tables. We can obtain an index of codes in the reconstructed VLC tables by simple arithmetic operations. In this method, the VLC tables are accessed just once in decoding a symbol. We modeled the proposed algorithm in C language, compiled under ARM ADS1.2 and simulated it with Armulator. Experimental results show that the proposed algorithm reduces execution time by about 80% and 15% compared with the H.264/AVC reference program JM(Joint Model) 10.2 and the arithmetic operation algorithm which is recently proposed, respectively.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.268-272
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• 2007

현재 시행되고 있는 하천정비와 하도정비는 하천 흐름의 특성을 간과한 채 일괄적으로 진행되어 왔으며 그 결과로 하천의 인공화는 지금까지 계속되고 있다. 이에 따라 하천 및 하도의 물리, 화학, 생물에 미치는 영향은 심각하며, 그 동안 인위적인 하천교란의 요인과 하천교란에 따른 영향, 즉 하상변동, 외래종 식생 침입, 생태서식처 변화 등의 정량적 평가 기술의 수립은 매우 미흡한 상태이다. 뿐만 아니라 하천 교란 극복을 위한 저감기술, 복원기술 및 적응관리 기술 또한 체계적으로 정리되지 못하여 하천과 댐 관리당국이 어려움을 겪고 있다. 이러한 상황을 극복하기 위해서는 하천 교란에 대항하는 회복관리 기술 개발을 위한 교란 평가 기술이 필요하다. 따라서 본 연구에서는 항공사진 및 GIS기법을 이용하여 국내 주요하천의 원인별 교란실태를 조사하고 분석함으로써 하천교란 조사기술 개발에 응용할 수 있는 방안을 제시하고자 하였다. 분석을 위하여 댐 하류의 하천교란 및 적응현장 시범지역을 선정한 후 대상 지역의 항공사진을 GIS화하여 하천 교란 실태를 분석하는 데에 필요한 자료를 생성하였으며 생성된 자료를 바탕으로 하천의 평면 및 단면의 변화특성을 조사할 수 있었다. 또한 경년별 저수로 형태와 하천 중심선 비교 분석을 통하여 저수로의 이동 및 변화 양상을 규명해 낼 수 있었으며 그 결과 댐 하류지역에서 하도안정문제가 발생하였음을 확인할 수 있었다. 본 연구 결과를 바탕으로 보다 효율적인 하도안정문제에 관한 대책수립이 가능하리라 보며, 이를 위해서는 하천 교란 조사기술 개발에 대한 연구가 뒤따라야 할 것이다.과적임을 알 수 있었다. 실험 결과 본 기법으로 유휴시간에 프로세서를 저전력모드로 바꾸는 기존의 고전적인 전력 관리 기법보다 전체 시스템 전력 소모를 9% 더 절약할 수 있었다. 위성영상과 DEM 개발기술이 87% 이상의 점수를 받아 가장 시장성 및 활용성이 높은 기술로 평가되었으며, 초다분광영상에 대한 기술은 70%를 겨우 넘는 수준에서 평가가 되었다. 멀티센서 공간영상정보 통합처리 기술 개발은 다목적 실용위성의 보유, 국가 NGIS 사업의 결과물이 상당히 축척이 되어 있고, 라이다(LiDAR) 기술의 도입을 위한 환경이 조성되었기에 다른 국가에 비해 멀티센서 기술의 적용과 산업화가 가시화 될 수 있을 것으로 기대된다. 그러나 멀티센서 자료의 수급이 용이하지 못하고, 법 제도적인 한계, 시장의 성숙도가 기대이하라는 점 등의 한계를 노정하고 있다.a var. sieboldii 3. Pinus densiflora, Q. aliena, Q. acutissima, P. thunbergii, Q. acuta 4. Carpinus laxiflora, Camellia japonicas. C. tschonoskii community의 5개 그룹으로 나타났다. 하류의 부착돌말류는 상대적으로 양호한 수질을 가지고 있는 정점 1에서 다양한 생물상을, 탄천의 영향을 받는 정점 2는 상대적으로 수질이 악화되어 호오염성 종들이 높은 분포를 나타내고 있었다. 또한 부착돌말류 중 Cymbella minuta는 다른 부착돌말류에 비해 강한 오염지표성을 나타내고 있었다.p=0.000, $4.76{\pm}3.31$