• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• Radiation Oncology Journal
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• 제18권4호
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• pp.345-354
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• 2000

목적 : 방사선조사야를 확인하는 보편적인 방법인 linacgram은 저대조도(low contrast)의 영상을 보여주고 있어 정확한 영상을 확인하는데 문제점이 있다. 따라서 본 연구는 linacgram의 대조도를 높이는 저가형 확인방법을 모색하여 영상판독과 조사야 확인에 도움이 되고자 한다. 대상 및 방법: 인체모형을 사용하여 얻어진 필름 영상을 필름전용 스캐너(Diagnostic Pro)를 통해 Optical Density Scan, Histogram Equalized, Linear Histogram Based (HB), Linear Histogram Independent, Linear Optical Density (OD) Logarithmic 및 Power, Square Root scan 방식으로 디지털화 하였다. 각기 다른 방식으로 전산 입력된 영상의 신호분포도를 얻어 signal intensity를 비교한 후 pailette fitting 방식을 통해 영상을 재구성하였고 재구성된 영상을 비교 분석하였다. 실제 치료에서 얻어진 각 인체 부위별 linacgram도 동일한 방법으로 처리한 후 화질 개선도를 알아 보았다. 결과 : 인체모형을 통해 얻어진 영상의 신호 분포영역은 Logarlthmic 방식을 선택했을 때 최소값인 3192가 나왔고 Square Root방식을 사용했을 때 최대값인 21940가 나왔다. 이러한 값들을 모니터 상에서 구현할 수 있는 256 gray scale로 바꾸어 보았을 때 7$\~$30$\%$ 만 사용되어지고 있음을 알수 있었다. Pallette fitting 방식을 통하여 모니터의 최대표현 값인 256 계조도로 Gray Scale Expansion (GSE) 함으로써 모니터가 지원하는 8bit gray scale pallette의 전범위를 사용하여 대조도가 개선되었다. 임상에서 얻어진 각 인체 부위별 무릎관절, 두경부, 폐, 골반영상에서도 GSE 처리하여 얻어진 영상이 해부학적 구조를 판독하는데 도움이 죄었다. 결론 : GSE 영상의 재구성은 대조도를 증가 시킬뿐 아니라 인체내 관심부위의 농도분포를 별도로 재구성할 수 있으므로 이중방사선조사(double exposure)에 의해 발생되는 화질의 저하를 보정함으로써 화질 개선을 가능하게 하였다. Linacgram 화질 개선은 simulation image 및 치료계획에서 발생한 DRR과 multi-layer 중첩영상 분석에 사용할 수 있으며 영상 비교 시 치료부위의 신속하고 정밀한 확인을 가능하게 하였다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1998년도 추계학술대회논문집:21세기에 대비한 지능형 통합항만관리
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• pp.211-221
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• 1998

A digital image processing technique which is able to get the velocity vector distribution of a surface of the spilled oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• 한국항만학회지
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• 제12권2호
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• pp.291-302
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• 1998

A digital image processing technique which is able to be used for getting the velocity vector distribution of a surface of the spilt oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Journal of Biosystems Engineering
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• 제27권4호
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• pp.341-348
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• 2002

Quality evaluation of red ginsengs is determined by outer shape and inner qualities. Especially, the inner qualities are main grading criteria. Currently, red ginsengs are classified into 3-grades; heaven, earth and good. The best heaven grade must not include inner holes and sponge tissues. This study was conducted to develop a red ginseng sorting system using x-ray image processing technique. Because of lens characteristic, gray values of the central region in the x-ray image are higher and gradually decreased towards the edge regions. This difference of gray values gives trouble in segmentation and detection of inner holes in red ginseng image, so preprocessing technique is necessary. The preprocessing was done by subtracting source image from an empty background image. But, simple subtraction was not quite appropriate because of too small contrast between inner holes and sound part. Scaled subtraction images were obtained by multiplying all gray values by some numbers. However this method could not help to set threshold value because the gray values of root part are generally lower than body part when red ginseng is exposed to the x-ray. To determine threshold value for detecting inner holes, an algorithm was developed by increasing overall gray values of less clear images.

• Journal of Mechanical Science and Technology
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• 제19권10호
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• pp.1856-1863
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• 2005

In this study, a visual sensor system for weld seam tracking the I-butt weld joints in GMA welding was constructed. The sensor system consists of a CCD camera, a diode laser with a cylindrical lens and a band-pass-filter to overcome the degrading of image due to spatters and arc light. In order to obtain the enhanced image, quantitative relationship between laser intensity and iris opening was investigated. Throughout the repeated experiments, the shutter speed was set at 1/1000 second for minimizing the effect of spatters on the image, and therefore the image without the spatter traces could be obtained. Region of interest was defined from the entire image and gray level of the searched laser stripe was compared to that of weld line. The differences between these gray levels lead to spot the position of weld joint using central difference method. The results showed that, as long as weld line is within $\pm15^{o}$ from the longitudinal straight line, the system constructed in this study could track the weld line successfully. Since the processing time is no longer than 0.05 sec, it is expected that the developed method could be adopted to high speed welding such as laser welding.

• 한국축산시설환경학회지
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• 제7권3호
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• pp.177-182
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• 2001

본 연구는 가축분뇨의 오염물질의 농도와 영상처리를 통해 얻어 낸 영상정보값과의 상관관계를 구하기 위해 수행하였다. CCD-카메라와 개인용 컴퓨터를 사용하여 축 분뇨의 영상을 받은 후 각 활성 영역에서의 영상정보와 공정시험 법으로 구한 오염물질과의 관계를 회귀분석법을 이용하여 다음과 같은 결론을 얻을 수 있었다. 1. 영상정보 R값은 CDD값과 결정계수가 0.9213으로 가장 높았으며, G값은 BOD값과 결정계수가 0.9019로 가장 높게 나타났으며, B값의 경우 오염물질 농도와의 상관관계는 매우 적은 것을 알 수 있었다. 2. H값은 BOD와의 결정계수($R^2$)가 0.9496으로 매우 높게 나타났다. 이는 BOD추정에 이용가능할 것으로 판단되었다. 3. BOD농도 추종을 위해서 G값,GRAY, H값, S값, 1값 등이 결정계수가 0.8이상을 나타냈으며, 그 중 H값이 가장 높은 결정계수를 나타냈으며, 이러한 정보를 이용하여 농도 추정이 가능할 것으로 판단되었다. 4. COD농도 추정을 위해서 R값, GRAY값, S값이 0.8이상의 결정계수를 나타냈으며, 그 중에서 R값과의 관계가 가장 높게 나타났으며, 이를 이용하여 간접적으로 농도 추정이 가능할 것으로 판단되었다. 5. SS농도와 영상정보값과 결정계수가 모두 0.8이하로 나타났으며, $NH_4$-N와 $NO_3$-N의 농도와 영상정보와의 결정계수는 모두 0.2이하로 매우 낮게 나타났으며, 가시광선영역의 CCD-카메라를 이용한 농도추정은 불가능할 것으로 판단되었다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.