• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.133-136
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• 2000

에너지 차분 흥부 X선 화상으로부터 폐종류 음영을 검출하기 위한 필터를 예측해서 전문의의 진단보조 혹은 총합자동진단시스템의 구성 요소로서 필터가 발휘한 역할을 고려한 후, 구체적인 성능 평가 방법을 제안한다. 필터의 성능을 평가할 때 문턱값을 변화시킨 경우, 못보고 빠트린 비율과 잘못 본 비율의 변화를 ROC 곡선으로 나타내어 이것에 기초한 판단을 행하는 접근방법이 있다. 본 연구에서는 이와같은 평가에 대한 구체적인 예를 통하여 문제점을 명확히 하여 그 평가기준을 마련한다. 성능 평가를 행하기 위해 이용된 에너지 차분화상으로서, 임상 데이터 14개의 증예를 이용한다. 즉, 총 종류수 32개 한 개의 증예에 있어서 종류의 개수는 1~8개로 평균 2개, 1mm 당 샘플링 간격 5 픽셀, 비트 분해능 10 bit의 저압화상으로, 그 크기는 1760$\times$1760이다. 계산기 하드웨어의 제약으로부터 원화상을 가우스 함수로 평활화 해서 1/8로 축소한 화상으로 실험을 행한다. 상기 평가 절차에 따라, 이전에 개발된 다중해상도 ∇$^2$G 필터의 성능을 평가하고, 단일해상도 ∇$^2$G 필터와의 비교를 통해 그 성능이 우수함을 확인한다. 본 평가 방법은 화상진단 지원용 필터의 평가에 대해서 적용될 수 있을 것이다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.261-264
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• 2001

논문에서는 S+P 웨이브릿 변환과 정수 웨이브릿 필터들을 비교 분석하고, 9/7텝 정수 웨이브릿 필터를 이용하여 웨이브릿 변환을 하고, 점진적 전송에 적합 하고, 다중 분해능 구조의 종속성과 방향성에 대한 고려와 예측오차의 피드백을 이용한 컨텍스트 모델링 예측과 적응산술부호화에 의한 엔트로피 코딩 방법을 제안하였다. 다양한 영상들에 대한 실험을 통해 본 논문에서 제안한 무손실 영상 압축알고리즘을 S+P 웨이브릿을 이용한 결과와 비교하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.199-205
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• 2018

So many fast motion estimation algorithms for prediction quality and computational reduction have been published due to tremendous computations of full search algorithm. In the paper, we suggest an algorithm that reduces computation effectively, while keeping prediction quality as almost same as that of the full search. The proposed algorithm based on multiple threshold filter calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, removes impossible candidates, and calculates optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain the better performance of calculation speed by reducing unnecessary computations. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.487-494
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• 2011

Data Fusion algorithm is essential in Target Detection using radar, and it has more reliability. In this paper, Multi Radar Fusion algorithm using IMM(Interacting Multiple Model) filter is suggested. This well-known IMM filter has better performance than Kalman filter has. In this simulation, Distributed Data Fusion process was applied, and three sub-filters and one main filter were employed. In addition, this simulation was evaluated by virtual radar data which include constant velocity, constant accelerate, turn rate. The result of an evaluation shows better performance in the maneuvering section of aircraft.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.141-148
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• 2021

In this paper, we propose an algorithm of welding bead detection and evaluation using geodesic active contour algorithm and high pass filter with image processing technique. The algorithm uses histogram equalization and high pass filter as gaussian filter to improve contrast. The image processing techniques smoothens the welding beads reduce the noise on an image. Then, the algorithm detects the welding bead area by applying the geodesic active contour algorithm and morphological ooperation. It also applies the balloon force that either inflates in, or deflates out the evolving contour for a better segmentation. After that, we propose a method for determining the quality of welding bead using effective length and width of the detected bead. In the experiments, our algorithm achieved the highest recall, precision, F-measure and IOU as 0.9894, 0.9668, 0.9780, and 0.8957 respectively. We compared the proposed algorithm with the conventional algorithms to evaluate the performance of the proposed algorithm. The proposed algorithm achieved better performance compared to the conventional ones with a maximum computational time of 0.6 seconds for segmenting and evaluating one welding bead.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.190-196
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• 2015

In this paper, we propose multiple location error compensation algorithm for GPS/INS fusion using kalman filter and introduce the way to reduce location error in 9-axis navigation devices for implementing inertial navigation technique. When evaluating location, there is an increase of location error. So navigation systems need robust algorithms to compensate location error in GPS/INS fusion. In order to improve robustness of 9-axis inertial sensor(mpu-9150) over its disturbance, we used tilt compensation method using compensation algorithm of acceleration sensor and Yaw angle compensation to have exact azimuth information of the object. And it shows improved location result using these methods combined with kalman filter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.93-100
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• 2006

This paper presents a multi-sensor data simulator and a data fusion algorithm for tracking high dynamic flight target from Radar and Telemetry System. The designed simulator generates time-asynchronous multiple sensor data with different data rates and communication delays. Measurement noises are incorporated by using realistic sensor models. The proposed fusion algorithm is designed by a 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad data and sensor faults. The designed algorithm is verified by using both simulation data and actual real data.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.7-14
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• 2000

Recently, the technologies of adaptive noise cancellation(ANC) are developed fast and widely due to the highly sophisticated digital signal processing algorithms and the high-speed communication networks and devices. But, thousand numbers of the adaptive filter taps are required to obtain the satisfying results in the fields of the adaptive noise cancellation and echo cancellation. In the paper, performance comparisons based on the real-time processing between frequency domain adaptive filter(FDAF) and multi-delay frequency domain adaptive filter(MDF) are carried. Those algorithms provide us with the reductions of the computational burdens and the increase of the convergence rate for the lengthy Fill adaptive filters. The time delay due to the long taps of FDAF can be reduced by adopting the MDF algorithms. The conventional ANC and cross talks ANC using FDAF are implemented on the dSP ACE 1103 real-time signal processing board.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.1-8
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• 2020

The need for storage, management, and retrieval techniques for alternative data has emerged as technologies based on data generated from business activities conducted by enterprises have emerged as the key to business success in recent years. Existing big data platform systems must load a large amount of data generated in real time without delay to process unstructured data, which is an alternative data, and efficiently manage storage space by utilizing a deduplication system of different storages when redundant data occurs. In this paper, we propose a multi-layer distributed data deduplication process system using the similarity of the Cuckoo hashing filter technique considering the characteristics of big data. Similarity between virtual machines is applied as Cuckoo hash, individual storage nodes can improve performance with deduplication efficiency, and multi-layer Cuckoo filter is applied to reduce processing time. Experimental results show that the proposed method shortens the processing time by 8.9% and increases the deduplication rate by 10.3%.