• Journal of Korea Multimedia Society
• /
• v.13 no.3
• /
• pp.410-416
• /
• 2010

This paper presents the auto-extraction method that searches for the Mapping points in the calibration algorithm of the image acquired by the wide angle CCD camera. In this algorithm, we remove the noise from the distorted image and then obtain the edge image. Proposed method extracts the distortion point, comparing the threshold value of the histogram of the horizontal and vertical pixel lines in edge image. This processing step can be directly applied to the original image of the wide angle CCD camera output. Proposed method results are compared with hand-worked result image using the two wide angle CCD cameras having different angles with the difference value of the result images respectively. Experimental results show that proposed method can allocate the distortion-calibration constant of the wide angle CCD camera regardless of lens type, distortion shape and image type.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.986-989
• /
• 2003

In the steel production line, the molten metal of a furnace is transformed into slab material and then move to the hot strip line, This paper describe about the real time recognition system of material management number, which is marked at the surface of a slab in the steel production line. This recognition processing should be performed before the slab is moved to the hot strip line. This system include following recognition steps. First, we remove noise from the captured slab image by use pre-filter. Second, we extract rough area, which is include slab number and then, we extract individual number area. Finally, we recognize material management number by use KLT(Karhunen-Loeve transform) algorithm. We applied our system to the real slave image, which was captured in the process line. In the results, we recognized slave number to the 94% accuracy.

• Bulletin of the Korean Space Science Society
• /
• 2009.10a
• /
• pp.42.1-42.1
• /
• 2009

한국천문연구원은 우주측지용 레이저 추적 시스템 개발 사업 중 현재 이동형 시스템(ARGO-M) 1기를 개발 중에 있으며, 2009년 5월에 시스템 개념 설계 검토(SDR) 회의를 수행하였고 현재는 예비 설계 단계를 진행 중이다. ARGO-M을 구성하는 5개의 서브시스템 중 하나인 운영시스템은 레이저 관측에 필요한 각종 서브시스템을 제어하고 환경을 종합 판단 후 이를 관측에 반영하며, 실제 관측을 통해 획득한 데이터를 통합 처리 및 전송하는 역할을 담당하고 있다. 현재 본격적인 예비 설계 수행 단계에 있는 운영시스템은 우선적으로 핵심이 되는 소프트웨어의 설계를 위해 오스트리아의 Graz에 위치한 IWF(Institut fur Weltraumforschung) 소속 SLR(Satellite Laser Ranging) 관측소를 2009년도에 방문하여 운영 전반에 관련한 소프트웨어의 로직분석 작업을 수행하였다. Graz 운영시스템 중 소프트웨어관련 시스템은 크게 KHz급 반복율을 가진 레이저를 사용하여 위성까지의 거리 측정에 해당되는 실시간 시스템과 실시간 측정을 통해 저장된 관측 원시 자료를 이후 분석을 수행하는 비 실시간(Non-real time) 시스템으로 나눌 수 있다. 이 중에서 비 실시간 시스템은 원시 자료 분석을 통해 시간 및 거리 바이어스 적용, 노이즈 제거 등의 후처리 과정과 다양한 통계 분석 그리고 SLR시스템의 최종 산출물인 정규점(Normal Point) 생성 등을 수행한다. 이번 소프트웨어 분석 연구를 통해 얻어진 주요 알고리즘과 다양한 다이어그램을 포함한 결과물은 ARGO-M 운영시스템에 최적화하도록 소프트웨어 재구성 및 개발에 반영할 예정이다.

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.120-126
• /
• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.1
• /
• pp.83-90
• /
• 2018

In this paper, we propose an algorithm for analyzing personal health log information in android environment, providing personal health log information in android environment, providing personalized exercise information and monitoring the condition of pedestrians. Personal health log data collection is performed based on raw data of user using MPU6050 sensor based on Arduino. Noise was removed and age threshold was applied to distinguish movement information. In addition, to protect personal information, safety is enhanced by providing anti-compilation prevention and encryption/decryption of APK file, and the result of movement information collection is measured according to sensor location. Experimental results showed that the MPU6050 sensor mounted one the ankle wsa measured 98.97% more accurately then the wrist. In addition, the loading time of SEED 128 bit encryption based DEX file has the average time of 0.55ms, minimizing the overhead.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.530-533
• /
• 2009

This paper proposes a method of recognizing that a person doesn't put on a safety cap using image processing method in DSP(Digital Signal Processor). It processes inputted images by image input devices that equipped in a industrial settings. If the method recognizes a person that doesn't put on a safety cap, a system transfers relevant recognition result to a supervisor and takes proper measures. If an accident happens and someone doesn't put on a safety cap, additional casualities could be. Proposed method can nip additional casualties in the bud. To recognize that a person don't put on a safety cap, images are processed by object abstraction, removal of noise, decision of a thing or a person, abstraction of a head part in a image, recognizing whether a man puts on a safety cap using HSV color space or not, and so on. Image input and image process are processed by DSP. And C language-based codes are optimized by an eignefunction(Intrinsics) for speed improvement of algorithms.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.6
• /
• pp.21-27
• /
• 2018

Wearing degree and uneven wearing detection algorithm using horizontal edge information is proposed in this paper. The noise in the input image is removed by bilateral filter, and then edges are extracted from the filtered image by using the proposed mask. As the tire is worn, grooves of tire shoulder or sipes are changed more than the vertical grooves. Therefore the edges from grooves of tire shoulder or sipes have more information about the tire wearing than the edges from vertical grooves. Proposed mask that is reflected this feature is used to extract the horizontal edges. After edge extraction, the edge image is represented in two-level system. The edge pixels of the binarization image are used to decide the wearing degree and uneven wearing. This proposed method can be used easily without any other equipments. The proposed method is conducted with a real vehicle, and the experimental results show the good performance of the proposed method in detecting wearing degree and uneven wearing.

• Journal of the Society of Disaster Information
• /
• v.14 no.4
• /
• pp.440-449
• /
• 2018

Purpose: This study aims to design and verify an onsite EEWS that extracts the P-wave from a single seismic station and deduce the PGV. Method: The P-wave properties of Pd, Pv, and Pa were calculated by using 12 seismic waveform data extracted from historic seismic records in Korea, and the PGVs were computed using empirical equation on the P properties - PGV relationship and compared with the observed values. Results: Comparison of the observed and estimated PGVs within the alarm level shows the error rate of 86.7% as minimum. By reducing the PTW to 2 seconds, the alarm time can be shortened by 1 second and the seismic blind zone near the epicenter can be shortened by 6 Km. Conclusion: Through this study, we confirmed the availability of the on-site EEWS in Korea. For practical use, it is necessary to develop regression formula and algorithm reflect local effect in Korea by increasing the number of seismic waveform data through continuous observation, and to eliminate the noise from the site.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.395-396
• /
• 2009

Electron tomography를 이용한 3차원적 영상 시각화는 electron microscopy를 통해 하나의 실험 대상으로부터 연속된 이미지를 생산함으로써 이루어진다. 이미지 데이터 내부에는 대용량의 정보값을 포함하고 있어 3차원 구조물로의 변환이 가능하다. electron tomography 작업 과정 중 고해상도 원본 이미지에 pattern recognition 알고리즘이 적용된 필터링을 적용하면 실험에 필요한 데이터의 정보 손실을 최소화한 상태에서 electron tomography 시스템의 효율성을 높일 수 있다. 또한 tomographic econstruction이 진행되는 각 단계에 hanning windowing을 적용하면 불필요한 정보 값이나 노이즈 등을 효과적으로 제거할 수 있다. 윤곽선 데이터의 효과적 활용을 위하여 sobel 필터 처리를 할 경우 관찰하고자 하는 대상의 윤곽선 특징을 뚜렷하게 시각화 할 수 있었다. 본 연구를 통하여 데이터의 시각화 과정에서 실험의 신뢰성 확보를 위해 원본 이미지를 기반으로 하는 tomogram과 필터링을 적용한 tomogram을 비교하여 최종 결과물의 정확도를 높이고, electron tomography를 통한 결과물의 질적 향상을 유도할 수 있음을 확인하였다.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.907-917
• /
• 2023

Recently, a self-driving car have applied deep learning technology to advanced driver assistance system can provide convenience to drivers, but it is shown deep that learning technology is vulnerable to adversarial evasion attacks. In this paper, we performed five adversarial evasion attacks, including MI-FGSM(Momentum Iterative-Fast Gradient Sign Method), targeting the object detection algorithm YOLOv5 (You Only Look Once), and measured the object detection performance in terms of mAP(mean Average Precision). In particular, we present a method applying morphology operations for YOLO to detect objects normally by removing noise and extracting boundary. As a result of analyzing its performance through experiments, when an adversarial attack was performed, YOLO's mAP dropped by at least 7.9%. The YOLO applied our proposed method can detect objects up to 87.3% of mAP performance.