• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.817-827
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• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.31-39
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• 2003

The MPEG-2 source coding algorithm is very sensitive to transmission errors due to using of variable-length coding. When the compressed data are transmitted, transmission errors are generated and error correction scheme is not able to be corrected well them. In the decoder error concealment (EC) techniques must be used to conceal errors and it is able to minimize degradation of video quality. The proposed algorithm is method to conceal successive macroblock errors of I-frame and utilize temporal information of B-frame and spatial information of P-frame In the previous GOP which is temporally the nearest location to I-frame. This method can improve motion distortion and blurring by temporal and spatial errors which cause at existing error concealment techniques. In network where the violent transmission errors occur, we can conceal more efficiently severe slice errors. This algorithm is Peformed in MPEG-2 video codec and Prove that we can conceal efficiently slice errors of I-frame compared with other approaches by simulations.

• Journal of Biomedical Engineering Research
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• v.19 no.6
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• pp.585-593
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• 1998

In Fourier magnetic resonance imaging (MRI), the number of phase encoded signals is often reduced to minimize the duration of the studies and maintain adequate signal-to-noise ratio. However, this results in the well-known truncation artifact, whose effect manifests itself as blurring and ringing in the image domain. In this paper, we propose a new regularization method in the context of a Bayesian framework to reduce truncation artifact. Since the truncation artifact appears in t도 phase direction only, the use of conventional piecewise-smoothness constraints with symmetric neighbors may result in the loss of small details and soft edge structures in the read direction. Here, we propose more elaborate forms of constraints than the conventional piecewise-smoothness constraints, which can capture actual spatial information about the MR images. Our experimental results indicate that the proposed method not only reduces the truncation artifact, but also improves tissue regularity and boundary definition without oversmoothing soft edge regions.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2017.05a
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• pp.121-121
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• 2017

본 연구는 비전도성 폴리머 표면을 개질하여 감광성 금속을 유전체 표면에 흡착시키고, 감광성 금속의 광화학 반응을 이용하여 귀금속 촉매를 비전도성 폴리머 표면에 선택적으로 흡착시켜 무전해 Cu 도금을 수행하여 금속패턴을 형성하였다. 기능성 유연 필름은 일반적으로 투명한 플라스틱 고분자 기판을 기반으로 전기 전자, 에너지, 자동차, 포장, 의료 등 다양한 분야에서 폭넓게 활용 되고 있으며, 본 연구에서는 습식 도금 공정을 이용하여 폴리이미드 필름상에 $10{\mu}m$ 이하의 미세패턴을 형성하기 위한 공정을 개발하고자 하였다. 비전도성 폴리머 표면에 무전해 도금을 위해서 우선 폴리머 필름의 표면을 개질하는 공정이 필요하다. 이에 KOH 또는 NaOH 알카리 용액을 이용하여 표면을 개질하였으며 개질된 표면에 감광성 금속이온의 흡착시키기 위한 감광성 금속이온은 주석을 사용하였으며, 주석 용액의 안정성 및 퍼짐성 향상을 위해 감광성 금속 용액의 제조 및 특성을 관찰하였으며, 감광성 금속화합물이 흡착된 비전도성 유전체 표면을 포토마스크를 이용하여 특정 부위, 즉 표면에 금속패턴 층을 형성하고자 하는 곳은 포토마스크를 이용하여 광원을 차단하고 그 외 부분은 주 파장이 365nm와 405nm 광원을 조사하여 선택적으로 감광성 금속화합물의 산화반응을 유도하는 광조사 공정을 수행하였다. 광원이 조사되지 않은 부분에 귀금속 등의 촉매 입자를 치환 흡착시켜 금속 패턴이 형성될 수 있는 표면을 형성하였다. 위의 활성화 공정이후에 활성화 처리된 표면을 세척하는 수세 공정을 거친 후 무전해 도금공정에 바로 적용할 경우 미세한 귀금속 입자가 패턴이 아닌 부분 즉 자외선(UV) 조사된 부분에도 남아있어 도금시 번짐 현상이 발생한다. 이에 본 연구에서는 활성화 처리 후 약 알칼리 용액에 카르복실산을 혼합하여 잔존하는 귀금속 입자를 제거한 후 무전해 Cu 도금액을 이용하여 $10{\mu}m$ 이하의 Cu 금속 패턴을 형성하였다.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.40-46
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• 2020

As interest in traffic safety increases, research on autonomous driving, which reduces the incidence of traffic accidents, is increased. Object recognition and detection are essential for autonomous driving. Therefore, research on object recognition and detection through traffic image big data is being actively conducted to determine the road conditions. However, because most existing studies use only daytime data, it is difficult to recognize objects on night roads. Particularly, in the case of a light source object, it is difficult to use the features of the daytime as it is due to light smudging and whitening. Therefore, this study proposes Yolo based light source object detection for traffic image big data processing. The proposed method performs image processing by applying color model transitions to night traffic image. The object group is determined by extracting the characteristics of the object through image processing. It is possible to increase the recognition rate of light source object detection on a night road through a deep learning model using candidate group data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.958-964
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• 2010

Histogram Equalization(HE) is one of the well known methods for contrast enhancement. but, it did not applied directly due to side effects such as significant change in brightness or washed out appearance. Many conventional method try to overcome this problem but they did not guarantee various image or depend on user define parameter. In this paper, an Adaptive histogram Compensated Histogram Equalization(ACHE) is proposed for contrast enhancement. ACHE has a parameter that based on median of input image. Histogram of input image is compensated according to parameter. And then finally compensated histogram is equalized. Experimental results show that proposed method suppresses side effects such as detail loss or washed out appearance. Moreover, parameter calculated automatically with low computation complexity. As a result, it could applies FPD directly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.