• International Journal of Aeronautical and Space Sciences
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• v.1 no.2
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• pp.17-21
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• 2000

In order to correct the strut interference in wind tunnel tests, image methods are conventionally used. Because of their excessive extra runs, some alternatives have been tried to reduce the extra runs. In this study, these alternatives were reviewed and checked by the strut interference evaluation with the panel code, CMARC. The present work shows that the strut interference is free from neither model configuration nor model attitude. This dependency makes the alternatives to the image method unfeasible. The 3-run image method was also evaluated. It worked well even for the exaggerated windshield. At this point, reducing the image runs by neglecting parameters affecting minor influence would be best.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.37-43
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• 2009

In this paper, we proposed that a novel method base on a binary image that technique is proposed for data hiding into binary images and halftone image. A binary image is bitmap image and halftone is composed by two-tone value in a limited region in an image. For this reason, it is not easy to hide messages in binary images. PWLC is a new method to hide a message in binary images. However, it yields images of unacceptable quality, unless you should change very few of it. Therefore, in order to solve this problem, we used run-length method into binary images. That is, we find a proper region to hide messages. In this paper, we proposed new method to hide messages in binary images. In addition, we proved that our algorithm is better than PWLC through the experiment.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.199-210
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• 1998

In this paper, we present a 3D reconstruction method of color volume data for a computerized human atlas. Binary volume rendering which takes the advantages of object-order ray traversal and run-length encoding visualizes 3D organs at an interactive speed in a general PC without the help of specific hardwares. This rendering method improves the rendering speed by simplifying the determination of the pixel value of an intermediate depth image and applying newly developed normal vector calculation method. Moreover, we describe the 3D boundary encoding that reduces the involved data considerably without the penalty of image quality. The interactive speed of the binary rendering and the storage efficiency of 3D boundary encoding will accelerate the development of the PC-based human atlas.

• Journal of Korea Multimedia Society
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• v.2 no.2
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• pp.155-165
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• 1999

Because the encrypted data is random, there is a possibility of threat that attacker reveals the secret data. On the other hand, as the image steganogrphy is to embed the secret data into cover image and to transmit the embedded image to receiver, an attacker could not know the existence of secret data even though he/she sees the embedded image, therefore the sender may reduce the threat of attack. In the image steganography, the secret data is embedded by modifying value of pixels as a form of noise. If the secret data is embedded into gray image, the degradation of image quality results from the modifications of image due to noise. Therefore many methods have been proposed to embed the secret data while dethering the gray image, but the existing method using error-diffusion has a problem that any patterns such as a diagonal lines or vertical take place due to embedding the secret data at the fixed interval. To solve this problem and to improve the existing method, we proposed the new method that embeds the secret data at changed point with respect to 1's run-length or at the position where has the minimum difference with the original dithered value. We evaluated the performance of the proposed method by computer simulation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.24-29
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• 2004

The grinding process plays a key role which decides the quality of a product finally. But the grinding process is very irregular, so it is very difficult to analyse the process accurately. Therefore it is very important in the aspect of precision and automation to reduce the idle time and to decide the proper dressing time by watching. In this study, we choose the method which can be observed directly by using of computer vision and then apply pattern classification technique to the method of measuring the wheel surface. Pattern classification technique is proper to analyse complicated surface image. We observe the change of the wheel surface by using of the gray level run lengths which are representative in this technique.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1285-1295
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• 1999

본 논문은 방대한 크기의 볼륨 데이타를 효율적으로 렌더링하기 위한 셀 기반 웨이브릿 압축 방법을 제시한다. 이 방법은 볼륨을 작은 크기의 셀로 나누고, 셀 단위로 웨이브릿 변환을 한 다음 복원 순서에 따른 런-길이(run-length) 인코딩을 수행하여 높은 압축율과 빠른 복원을 제공한다. 또한 최근 복원 정보를 캐쉬 자료 구조에 효율적으로 저장하여 복원 시간을 단축시키고, 에러 임계치의 정규화로 비정규화된 웨이브릿 압축보다 빠른 속도로 정규화된 압축과 같은 고화질의 이미지를 생성하였다. 본 연구의 성능을 평가하기 위하여 {{}} 해상도의 볼륨 데이타를 압축하여 쉬어-？ 분해(shear-warp factorization) 알고리즘에 적용한 결과, 손상이 거의 없는 상태로 약 27:1의 압축율이 얻어졌고, 약 3초의 렌더링 시간이 걸렸다.Abstract This paper presents an efficient cell-based wavelet compression method of large volume data. Volume data is divided into individual cell of {{}} voxels, and then wavelet transform is applied to each cell. The transformed cell is run-length encoded according to the reconstruction order resulting in a fairly good compression ratio and fast reconstruction. A cache structure is used to speed up the process of reconstruction and a threshold normalization scheme is presented to produce a higher quality rendered image. We have combined our compression method with shear-warp factorization, which is an accelerated volume rendering algorithm. Experimental results show the space requirement to be about 27:1 and the rendering time to be about 3 seconds for {{}} data sets while preserving the quality of an image as like as using original data.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.160-165
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• 2018

This paper designed and developed the image processing system of integrating feature extraction and matching by using convolutional neural network (CNN), rather than relying on the simple method of processing feature extraction and matching separately in the image processing of conventional image recognition system. To implement it, the proposed system enables CNN to operate and analyze the performance of conventional image processing system. This system extracts the features of an image using CNN and then learns them by the neural network. The proposed system showed 84% accuracy of recognition. The proposed system is a model of recognizing learned images by deep learning. Therefore, it can run in batch and work easily under any platform (including embedded platform) that can read all kinds of files anytime. Also, it does not require the implementing of feature extraction algorithm and matching algorithm therefore it can save time and it is efficient. As a result, it can be widely used as an image recognition program.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.179-184
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• 2004

This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.91-102
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• 1994

For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.115-122
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• 2008

Wu and Tsai's pixel-value differencing method and Chang and Tseng's side-match method are based on the theory that the number of bits which can be embedded is determined by the degree of the pixel's smoothness, or its proximity to the edge of the image. If pixels are located in the edge area, they may tolerate larger changes than those in smooth areas. However, both methods are subject to the fall off the boundary problem(FOBP). This study proposes a new scheme that can solve the FOBP. The experimental results demonstrate that the proposed method resolves the problem, and achieves a higher image quality index value than other methods.