• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.6
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• pp.33-43
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• 2003

In this paper, we proposed a real-time watermarking algorithm to be combined and to work with a DWT(Discrete Wavelet Transform)-based image compressor. To reduce the amount of computation in selecting the watermarking positions, the proposed algorithm uses a pre-established look-up table for critical values, which was established statistically by computing the correlation according to the energy values of the corresponding wavelet coefficients. That is, watermark is embedded into the coefficients whose values are greater than the critical value in the look-up table which is searched on the basis of the energy values of the corresponding level-1 subband coefficients. Therefore, the proposed algorithm can operate in a real-time because the watermarking process operates in parallel with the compression procession without affecting the operation of the image compression. Also it improved the property of losing the watermark and the efficiency of image compression by watermark inserting, which results from the quantization and Huffman-Coding during the image compression. Visual recognizable patterns such as binary image were used as a watermark The experimental results showed that the proposed algorithm satisfied the properties of robustness and imperceptibility that are the major conditions of watermarking.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.191-199
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• 2010

Physical modeling is a synthesis method of high quality sound which is similar to real sound for musical instruments. However, since physical modeling requires a lot of parameters to synthesize sound of a musical instrument, it prevents real-time processing for the musical instrument which supports a large number of sounds simultaneously. To solve this problem, this paper proposes a single instruction multiple data (SIMD) parallel processor that supports real-time processing of sound synthesis of guitar, a representative plucked string musical instrument. To control six strings of guitar, we used a SIMD parallel processor which consists of six processing elements (PEs). Each PE supports modeling of the corresponding string. The proposed SIMD processor can generate synthesized sounds of six strings simultaneously when a parallel synthesis algorithm receives excitation signals and parameters of each string as an input. Experimental results using a sampling rate 44.1 kHz and 16 bits quantization indicate that synthesis sounds using the proposed parallel processor were very similar to original sound. In addition, the proposed parallel processor outperforms commercial TI's TMS320C6416 in terms of execution time (8.9x better) and energy efficiency (39.8x better).

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.1-9
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• 2006

In this paper, we propose a MIMO-OFDMA (Multi Input Multi Output-Orthogonal Frequency Division Multiple Access) system based on beamforming for performance improvement of downlink real-time traffic transmission in harsh channel conditions with low CIR (Carrier-to-Interference Ratio). In the proposed system, we first consider the M-GTA-SBA (Modified-Grouped Transmit Antenna-Simple Bit Allocation) using effective CSI (Channel State Information) calculation procedure based on spatial resource grouping, which is adequate for the combination of MRT (Maximum Ratio Transmission) in the transmitter and MRC (Maximum Ratio Combining) in the receiver. In addition, to reduce feedback information for the beamforming, we also apply QEGT (Quantized Equal Gain Transmission) based on quantization of amplitudes and phases of beam weights. Furthermore, considering multi-user environments, we propose the P-SRA (Proposed-Simple Resource Allocation) algorithm for fair and efficient resource allocation. Simulation results reveal that the proposed MIMO-OFDMA system achieves significant improvement of spectral efficiency in low CRI region as compared to a typical open-loop MIMO-OFDMA system using pseudo-orthogonal space time block code and H-ARQ IR (Hybrid-Automatic Repeat Request Incremental Redundancy).

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.19-32
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• 2007

This paper present a new face recognition method based on LVQ neural net to construct a real time face recognition system. The previous researches which used PCA, LDA combined neural net usually need much time in training neural net. The supervised LVQ neural net needs much less time in training and can maximize the separability between the classes. In this paper, the proposed method transforms the input face image by PCA and LDA sequentially into low-dimension feature vectors and recognizes the face through LVQ neural net. In order to make the system robust to external light variation, light compensation is performed on the detected face by max-min normalization method as preprocessing. PCA and LDA transformations are applied to the normalized face image to produce low-level feature vectors of the image. In order to determine the initial centers of LVQ and speed up the convergency of the LVQ neural net, the K-Means clustering algorithm is adopted. Subsequently, the class representative vectors can be produced by LVQ2 training using initial center vectors. The face recognition is achieved by using the euclidean distance measure between the center vector of classes and the feature vector of input image. From the experiments, we can prove that the proposed method is more effective in the recognition ratio for the cases of still images from ORL database and sequential images rather than using conventional PCA of a hybrid method with PCA and LDA.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.604-609
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• 2014

Decoding processes in portable media players have a high computational cost, resulting in high power consumption by the CPU. If decoding computations are reduced, the power consumed by the CPU is also be reduced, but such a choice generally results in a degradation of the video quality for the users, so it is essential to address this tradeoff. We proposed a new CPU power management scheme that can make use of the scalability property available in the H.164/SVC standard. We first proposed a new video quality model that makes use of a video quality metric(VQM) in order to efficiently take into account the different quantization factors in the SVC. We then propose a new dynamic voltage scaling(DVS) scheme that can selectively combine the previous decoding times and frame sizes in order to accurately predict the next decoding time. We then implemented a scheme on a commercial smartphone and performed a user test in order to examine how users react to the VQM difference. Real measurements show that the proposed scheme uses up to 34% fewer energy than the Linux DVFS governor, and user tests confirm that the degradation in the quality is quite tolerable.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.149-154
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• 2004

In this research, we selected the speech recognition to implement the electric wheelchair system as a method to control it by only using the speech and used DTW (Dynamic Time Warping), which is speaker-dependent and has a relatively high recognition rate among the speech recognitions. However, it has to have small memory and fast process speed performance under consideration of real-time. Thus, we introduced VQ (Vector Quantization) which is widely used as a compression algorithm of speaker-independent recognition, to secure fast recognition and small memory. However, we found that the recognition rate decreased after using VQ. To improve the recognition rate, we applied ART2 (Adaptive Reason Theory 2) algorithm as a post-process algorithm to obtain about 5% recognition rate improvement. To utilize ART2, we have to apply an error range. In case that the subtraction of the first distance from the second distance for each distance obtained to apply DTW is 20 or more, the error range is applied. Likewise, ART2 was applied and we could obtain fast process and high recognition rate. Moreover, since this system is a moving object, the system should be implemented as an embedded one. Thus, we selected TMS320C32 chip, which can process significantly many calculations relatively fast, to implement the embedded system. Considering that the memory is speech, we used 128kbyte-RAM and 64kbyte ROM to save large amount of data. In case of speech input, we used 16-bit stereo audio codec, securing relatively accurate data through high resolution capacity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.401-404
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• 2015

This paper proposes a high-performance in-loop filter in HEVC(High Efficiency Video Coding) encoder for Ultra HD video processing in real time. HEVC uses in-loop filter consisting of deblocking filter and SAO(Sample Adaptive Offset) to solve the problems of quantization error which causes image degradation. In the proposed in-loop filter encoder hardware architecture, the deblocking filter and SAO has a 2-level hybrid pipeline structure based on the $32{\times}32CTU$ to reduce the execution time. The deblocking filter is performed by 6-stage pipeline structure, and it supports minimization of memory access and simplification of reference memory structure using proposed efficient filtering order. Also The SAO is implemented by 2-statge pipeline for pixel classification and applying SAO parameters and it uses two three-layered parallel buffers to simplify pixel processing and reduce operation cycle. The proposed in-loop filter encoder architecture is designed by Verilog HDL, and implemented by 205K logic gates in TSMC 0.13um process. At 110MHz, the proposed in-loop filter encoder can support 4K Ultra HD video encoding at 30fps in realtime.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.160-160
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• 2017

자동화 기술을 통한 한국형 스마트팜의 발전이 비약적으로 이루어지고 있는 가운데 무인화를 위한 지능적인 스마트 시설환경 관찰 및 분석에 대한 요구가 점점 증가 하고 있다. 스마트 시설환경에서 취득 가능한 시계열 데이터는 온도, 습도, 조도, CO2, 토양 수분, 환기량 등 다양하다. 시스템의 경계가 명확함에도 해당 속성의 특성상 타임도메인과 공간도메인 상에서 정확한 추정 또는 예측이 난해하다. 시설 환경에 접목이 증가하고 있는 지능형 관리 기술 구현을 위해선 시계열 공간 데이터에 대한 신속하고 정확한 정량화 기술이 필수적이라 할 수 있다. 이러한 기술적인 요구사항을 해결하고자 시도되는 다양한 방법 중에서 공간 분해능 향상을 위한 다지점 계측 메트릭스를 실험적으로 구성하였다. $50m{\times}100m$의 단면적인 연동 딸기 온실을 대상으로 $3{\times}3{\times}3$의 3차원 환경 인자 계측 매트릭스를 설치하였다. 1 Hz의 주기로 4가지 환경인자(온도, 습도, 조도, CO2)를 계측하였으며, 계측 하는 시점과 동시에 병렬적으로 공간통계법을 이용하여 미지의 지점에 대한 환경 인자들을 실시간으로 추정하였다. 선행적으로 50 cm 공간 분해능에 대응하기 위하여 Kriging interpolation법을 횡단면에 대하여 분석한 후 다시 종단면에 대하여 분석하였다. 3 Ghz에 해당하는 연산 능력을 보유한 컴퓨터에서 1초 동안 획득한 데이터에 대한 분석을 마치는데 소요되는 시간이 15초 내외로 나타났다. 이는 해당 알고리즘의 매우 높은 시간 복잡도(Order of $O=O^3$)에 기인하는 것으로 다양한 시설 환경의 관리 방법론에 적절히 대응하기에 한계가 있다 할 수 있다. 실시간으로 시간 복잡도가 높은 연산을 수행하기 위한 기술적인 과제를 해결하고자, 근래에 관심이 증가하고 있는 NVIDIA 사에서 제공하는 CUDA 엔진과 Apple사의 제안을 시작으로 하여 공개 소프트웨어 개발 컨소시엄인 크로노스 그룹에서 제공하는 OpenCL 엔진을 비교 분석하였다. CUDA 엔진은 GPU(Graphics Processing Unit)에서 정보 분석 프로그램의 연산 집약적인 부분만을 담당하여 신속한 결과를 산출할 수 있는 라이브러리이며 해당 하드웨어를 구비하였을 때 사용이 가능하다. 반면, OpenCL은 CUDA 엔진이 특정 하드웨어에서 구동이 되는 한계를 극복하고자 하드웨어에 비의존적인 라이브러리를 제공하는 것이 다르며 클러스터링 기술과 연계를 통해 낮은 하드웨어 성능으로 인한 단점을 극복하고자 하였다. 본 연구에서는 CUDA 8.0(https://developer.nvidia.com/cuda-downloads)버전과 Pascal Titan X(NVIDIA, CA, USA)를 사용한 방법과 OpenCL 1.2(https://www.khronos.org/opencl/)버전과 Samsung Exynos5422 칩을 장착한 ODROID-XU4(Hardkernel, AnYang, Korea)를 사용한 방법을 비교 분석하였다. 50 cm의 공간 분해능에 대응하기 위한 4차원 행렬($100{\times}200{\times}5{\times}4$)에 대하여 정수 지수화를 위한 Quantization을 거쳐 CUDA 엔진과 OpenCL 엔진을 적용한 비교한 결과, CUDA 엔진은 1초 내외, OpenCL 엔진의 경우 5초 내외의 연산 속도를 보였다. CUDA 엔진의 경우 비용측면에서 약 10배, 전력 소모 측면에서 20배 이상 소요되었다. 따라서 우선적으로 OpenCL 엔진 기반 하드웨어 가속 기술 최적화 연구를 통해 스마트 시설환경 실시간 시뮬레이션 기술 도입을 위한 기술적 과제를 풀어갈 것이다.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.549-558
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• 2001

It is important to reuse existing motion capture data for reduction of the animation producing cost as well as efficiency of producing process. Because its motion curve has no control point, however, it is difficult to modify the captured data interactively. The motion transition is a useful method to reuse the existing motion data. It generates a seamless intermediate motion with two short motion sequences. In this paper, Uniform Posture Map (UPM) algorithm is proposed to perform the motion transition. Since the UPM is organized through quantization of various postures with an unsupervised learning algorithm, it places the output neurons with similar posture in adjacent position. Using this property, an intermediate posture of two active postures is generated; the generating posture is used as a key-frame to make an interpolating motion. The UPM algorithm needs much less computational cost, in comparison with other motion transition algorithms. It provides a control parameter; an animator could control the motion simply by adjusting the parameter. These merits of the UPM make an animator to produce the animation interactively. The UPM algorithm prevents from generating an unreal posture in learning phase. It not only makes more realistic motion curves, but also contributes to making more natural motions. The motion transition algorithm proposed in this paper could be applied to the various fields such as real time 3D games, virtual reality applications, web 3D applications, and etc.