• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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• pp.181-184
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• 2003

예전의 영상처리 장비는 독립적으로 구현이 되었다고 하여도 단순히 디스플레이만 하는 정도였지만 현재 여러 가지 칩들의 발전으로 인한 그 응용에 있어 활용 범위가 다양해졌다. 본 연구에서는 아날로그 영상신호를 디지털로 컨버터 하여 PC없이 독립적으로 영상 데이터를 처리하는 시스템을 설계하고, 일반 아날로그 비디오 영상의 데이터에서 모션파라미터를 추출하여 시뮬레이터에 가상의 움직임을 만들어 낸다. 모션벡터를 추출하여 시뮬레이터를 구동하고, 영상 제어 알고리즘에 대하여 분석한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 하계학술대회 논문집
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.311-314
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• 1995

This paper presents a method for measuring tool wear parameters based on two dimensional image information. The tool wear images were obtained from an ITV camera with magnifying and lighting devices, and were analyzed using image processing techniques such as thresholding, noise filtering and boundary tracing. Thresholding was used to transform the captured gray scale image into a binary image for rapid sequential image processing. The threshold level was determined using a novel technique in which the brightness histograms of two concentric windows containing the tool wear image were compared. The use of noise filtering and boundary tracing to reduce the measuring errors was explored. Performance tests of the measurement precision and processing speed revealed that the direct method was highly effective in intermittent tool wear monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2881-2894
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• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• 한국산학기술학회논문지
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• 제10권7호
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• pp.1503-1508
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• 2009

본 논문은 열적외선 카메라 이미지를 영상 처리 기법을 활용하여 실시간으로 구현하는데 그 목적이 있다. 열적외선 영상 데이터는 온도의 변화에 따라 Hot Mapping, Cool Mapping, Rainbow Mapping을 하였으며, 열적외선 이미지의 명암대비 기능을 알아보기 위해 히스토그램 영상처리 기법을 사용하였고, 물체의 구분을 위해서 열적외선 이미지의 에지 부분을 추출하였다. 또한 이미지에서 온도를 추출해 내기 위해 이미지 정보 프로그램을 만들어 온도를 측정할 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1200-1202
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• 2003

Satellite and aerial images are very useful means to monitor ecological and environmental situation. Nowadays more and more officials at Ministry of Environment in Korea need to access and use these image data through networks like internet or intranet. However it is very hard to manage and service these image data through internet or intranet, because of its size problem. In this paper very large image data service system for Ministry of Environment is constructed on web environment using image compression and web based image processing technology. Through this system, not only can officials in Ministry of Environment access and use all the image data but also can achieve several image processing effects on web environment. Moreover officials can retrieve attribute information from vector GIS data that are also integrated with the system.

• 핵의학기술
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• 제12권1호
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• pp.13-18
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• 2008

목적: 다양한 algorism에 의한 영상처리기법은 핵의학 영상을 결정짓는 중요한 부분을 차지하고 있다. 이에 새로운 영상처리기법인 SIEMENS (made by pixon)사의 Onco. flash processing reconstruction을 적용하여 기존의 영상처리기법을 이용한 영상과 비교 분석함으로써 그 임상적 유용성을 평가한다. 대상 및 방법: 1) Scan speed의 차이에 의한 whole body bone scan을 시행하고, raw data와 processing data의 imaeg quality를 비교 분석하여 상대 평가한다. 2) Bone static scan을 acquisition count를 달리하여 시행하고, raw data와 processing data의 image quality를 비교 분석하여 상대 평가한다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가를 통한 image quality를 확인한다. 4) LSF을 통한 raw data와 processing data의 FWHM을 구하여 해상력 평가를 확인한다. 결과: 1) Whole body bone scan을 시행하여 본원 핵의학 판독의의 blinding test한 결과 scan speed 20 cm/min의 raw data와 30 cm/min의 processing data에는 임상 판독에 영향을 미칠 수준의 image quality 저하가 없었으나, 40 cm/min processing data는 영상 판독과 진단에 오류의 가능성을 배제 할 수 없는 image quality의 향상을 볼 수 없었다. 2) Bone static scan의 경우 200 kcts processing data는 200 kcts raw data보다 확실한 image quality의 향상을 가져왔으며 400 kcts raw data와 비교한 본원 핵의학 판독의 blinding test 결과 판독과 진단에 무리가 없을 수준의 유사한 image quality를 보였다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가는 processing을 통한 image quality의 향상을 확인할 수 있었다. 4) LSF을 통한 raw data와 processing data의 FWHM 평가 결과, resolution의 뚜렷한 증가나 감소의 확인은 할 수 없었다. 이는 noise level의 감소와 high S/N ratio 때문이라 판단된다. 결론: 기존의 영상과 비교 분석하여 평가한 결과 Onco. flash processing reconstruction을 적용한 경우 일정 수준까지 뚜렷한 image quality의 향상을 보였으며, 이는 장비 가동률의 상승과 환자 대기일수의 단축 그리고 저선량 검사에 따른 방사선 피폭에 대한 적극적 방어의 관점에서 현재 임상 핵의학에 충분한 유용성과 타당성이 있을 것으로 사료된다.

• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.17-26
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• 2012

This paper presents an image processing-based validation method for unrecognizable numbers in severely distorted license plate images which have been degraded by various factors including low-resolution, low light-level, geometric distortion, and periodic noise. Existing vehicle license plate recognition (LPR) methods assume that most of the image degradation factors have been removed before performing the recognition of printed numbers and letters. If this is not the case, conventional LPR becomes impossible. The proposed method adopts a novel approach where a set of reference number images are intentionally degraded using the same factors estimated from the input image. After a series of image processing steps, including geometric transformation, super-resolution, and filtering, a comparison using cross-correlation between the intentionally degraded reference and the input images can provide a successful identification of the visually unrecognizable numbers. The proposed method makes it possible to validate numbers in a license plate image taken under low light-level conditions. In the experiment, using an extended set of test images that are unrecognizable to human vision, the proposed method provides a successful recognition rate of over 95%, whereas most existing LPR methods fail due to the severe distortion.

• Journal of Biosystems Engineering
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• 제28권4호
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.