• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.654-654
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• 2004

본 논문에서는 이산웨이블렛 변환을 이용한 영상 압축 프로세서를 하드웨어로 구현하였다. 웨이블렛 변환을 위하여 필터뱅크 및 피라미드 알고리즘을 이용하였고 각 필터들은 FIR 필터로 구현하였다. 병렬구조로 이루어져 동일 클럭 싸이클에서 하이패스와 로패스를 동시에 수행함으로써 속도를 향상시킬 뿐 아니라 QMF 특성을 이용하여 DWT 연산에 필요한 승산기의 수를 절반으로 줄임으로써 하드웨어 크기를 줄이고 이용효율 또한 높일 수 있다. 다중 해상도 분해 시 필요한 메모리 컨트롤러를 하드웨어로 구현하여 DWT 계산이 수행되므로 이 융자는 단순한 파라메터 입력만으로 효과적인 압축율을 얻을 수 있도록 구조적으로 설계하였다. 실시간 영상압축 프로세서의 성능 예측을 위하여 MATLAB을 통하여 시뮬레이션 하였고, VHDL을 이용하여 각 모듈들을 설계하였다. 설계한 영상압축기는 Leonaro-Spectrum에서 합성하였고, ALTERA FLEX10KE(EPF10K100 EFC256) FPGA에 이식하여 하드웨어적으로 동작을 검증하였다. 설계된 부호화기는 512×512 Woman 영상에 대하여 33㏈의 PSNR값을 갖는다. 그리고 설계된 프로세서를 FPGA 구현 시 35㎒에서 정상적으로 동작한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.15-17
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• 2018

본 논문에서는 시장규모가 점진적으로 커지고 있는 VR의 콘텐츠 제작에 있어서 전방위 영상 생성을 위해 촬영한 영상들을 스티칭하는 데 소요되는 연산량을 감소시키는 방법을 제안한다. 제안하는 방법은 널리 사용되는 SIFT의 알고리즘에서 가장 많은 연산을 차지하는 가우시안 피라미드 생성 부분을 파라미터를 조절하여 감소시키고, 이를 통해 얻은 점들을 스티칭하는데 사용하여 영상을 합성하는 방법이다. 영상에 대한 평가는 변환에 의한 점들의 평균오차를 계산하여 유효성을 판단한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.703-704
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• 2023

학교폭력은 교육 환경에서 심각한 문제이다. 피해자에게 심리적 고통과 육체적 상해를 입히고 학교 내 안전과 안정성을 위협한다. 이에 많은 교육기관과 정부 기관이 학교폭력 예방과 대처를 위한 다양한 방안을 제시하고 있지만, 여전히 어려운 문제이다. 최근에는 인공지능 기술을 활용하여 학교폭력 방지와 대처에 관한 연구가 이루어지고 있다. 본 연구에서는 YOLOv5(You Only Look Once version 5) 딥러닝 알고리즘을 활용하여 학교 내부에서 발생하는 폭력 행위를 실시간으로 탐지하는 모델을 제안한다. 이 모델은 CCTV와 같은 영상 데이터를 입력으로 받아들여 학교 내부에서 발생하는 폭력 행위를 실시간으로 식별하는 것을 목표로 한다.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.12-18
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• 2012

Stereo correspondence is the central problem of stereo vision. In this paper, we propose a stereo matching scheme based on a genetic algorithm using a multi-resolution method and AD-Census. The proposed approach considers the matching environment as an optimization problem and finds the disparity by using a genetic algorithm And adaptive chronosome structure using edge pixels and crossover mechanism are employed in this technique. A cost function is composes of certain constraints whice are commonly used in stereo matching. AD-Census measure is applied to reduce disparity error. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement using local feature vector. We valid our method not only reduces the search time for correspondence compared with conventional GA-based method but also ensures the validity of matching.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.77-84
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• 2007

The intima media thickness(IMT) of the carotid artery from B mode ultrasound images has recently been proposed as the most useful index of individual atherosclerosis and can be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by manually tracing interfaces between tissue layers. The drawbacks of this method are the inter and intra observer variability and its inefficiency. In this paper, we present a multiresolution snake method combined with the dynamic programming, which overcomes the various noises and sensitivity to initialization of conventional snake. First, an image pyramid is constructed using the Gaussian pyramid that maintains global edge information with smoothing in the images, and then the boundaries are automatically detected in the lowest resolution level by minimizing a cost function based on dynamic programming. The cost function includes cost terms which are representing image features and geometrical continuity of the vessel interfaces. Since the detected boundaries are selected as initial contour of the snake for the next level, this automated approach solves the problem of the initialization. Moreover, the proposed snake improves the problem of converging th the local minima by defining the external energy based on multiple image features. In this paper, our method has been validated by computing the correlation between manual and automatic measurements. This automated detection method has obtained more accurate and reproducible results than conventional edge detection by considering multiple image features.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.431-447
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• 2021

Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.77-85
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• 2014

Medicine-bottle classification algorithm to avoid medicine accidents must be robust to a geometric change such as rotation, size variation, location movement of the medicine bottles. In this paper, we propose an algorithm to classify the medicine bottles exactly in real-time by using SIFT(Scale Invariant Feature Transform) which is robust to the geometric change. In first, we classify medicine bottles by size using minimum boundary rectangle(MBR) of medicine bottles as a striking feature in order to classify the medicine bottles. We extract label region in the MBR and the region of interest(ROI) considering rotation. Then, we classify medicine bottles using SIFT for the extracted ROI. We also simplify the number of octave of SIFT in order to improve a process speed of SIFT. We confirm to classify all the medicine bottles exactly as a result of performance evaluation of the proposed algorithm about images of 250 medicine bottles. We also confirm to improve the process time more than twice the processing time by simplifying the number of octave of SIFT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.465-469
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• 2017

In this paper we propose a human body tracking method for application of smartphones. The conventional human body tracking method is divided into a sensor-based method and a vision-based method. The sensor-based methods have a weakness in that tracking accuracy is low due to cumulative error of position information. The vision-based method has no cumulative error, but it requires reduction of the computational complexity for application of smartphone. In this paper we use the improved HOG algorithm as a human body tracking method for application of smartphone. The improved HOG algorithm is implemented through downsampling and frame sampling. Gaussian pyramid is applied for downsampling, and uniform sampling is applied for frame sampling. We measured the proposed algorithm on two devices, four resolutions, and four frame sampling intervals. We derive the best detection rate among downsampling and frame sampling parameters that can be applied in realtime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.948-956
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• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8455-8461
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• 2015

In this paper, we propose new search algorithms using SVD(Singular Value Decomposition) for fast search of Raman spectrum. In the proposed algorithms, small number of the eigen vectors obtained by SVD are chosen in accordance with their respective significance to achieve computation reduction. By introducing pilot test, we exclude large number of data from search and then, we apply partial distance search(PDS) for further computation reduction. We prepared 14,032 kinds of chemical Raman spectrum as the library for comparisons. Experiments were carried out with 7 methods, that is Full Search, PDS, 1DMPS modified MPS for applying to 1-dimensional space data with PDS(1DMPS+PDS), 1DMPS with PDS by using descending sorted variance of data(1DMPS Sort with Variance+PDS), 250-dimensional components of the SVD with PDS(250SVD+PDS) and proposed algorithms, PSP and PSSP. For exact comparison of computations, we compared the number of multiplications and additions required for each method. According to the experiments, PSSP algorithm shows 64.8% computation reduction when compared with 250SVD+PDS while PSP shows 157% computation reduction.