• Title/Summary/Keyword: Modified mask

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An Adaptive Region-of-Interest Coding Based on EBCOT (EBCOT 기반의 적응적 관심영역 코딩)

  • Kang, Ki-Jun;Lee, Bu-Kwon;Seo, Yeong-Geon
    • Journal of Korea Multimedia Society
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    • v.9 no.11
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    • pp.1445-1454
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    • 2006
  • To compress a specific part of an image with high quality or to transfer it, JPEG2000 standard offers an ROI(Region-of-Interest) image coding method. What is important in ROI coding is to process relative importance between ROI and background and to process ROI mask. We propose an adaptive ROI coding method supplemented the existing Implicit ROI coding and Modified implicit ROI coding to improve image quality and reduce ROI mask information. The proposed method is an EBCOT-based ROI coding that extracts ROI from the compressed bitstream, and gets the ROI mask information by classifying the codeblocks into 6 patterns. The information includes the pattern type(3bit) and the width(5bit) expressing the boundary between two regions for each codeblock. As a result, the method shows an excellent compression performance in ROI region as well as in the whole region of an image.

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A Modified Top-hat and Bottom-hat transform for Edge Detection (에지 검출을 위한 변형된 top-hat 및 bottom-hat 변환 알고리듬에 관한 연구)

  • Baek, Woon-Seok;Lee, Ha-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.9
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    • pp.901-908
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    • 2016
  • Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

A Study on Edge Detection Algorithm using Modified Morphology (변형된 모폴로지를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;An, Young-Joo;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.929-931
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    • 2015
  • As the digital image processing technology develops, the edge in the image is widely utilized in various fields such as the object recognition and detection. Most of the current methods to detect the edge use the fixed weighting mask of Sobel or Roberts. Such current methods have an advantage that the implementation is simple but have a disadvantage that the characteristics of the edge detection are more or less insufficient. Thus, an algorithm using the modified morphology is proposed in order to supplement such problems of the current edge detection methods and obtain the excellent edge detection, and also a simulation using this algorithm is conducted to compare with such current methods.

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A Study on Edge Detection for Images Corrupted by AWGN using Modified Weighted Vector (AWGN에 훼손된 영상에서 변형된 가중치 벡터를 이용한 에지검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.7
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    • pp.1518-1523
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    • 2012
  • Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.

Modified Adaptive Switching Median Filter using Noise Density in Salt and Pepper Noise Environment (Salt and Pepper 잡음 환경에서 잡음 밀도를 이용한 변형된 적응 스위칭 메디안 필터)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.916-918
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    • 2015
  • Image processing is being spotlighted as an important sector with increasingly diverse applications as the society advances into a sophisticated digital information age. Especially, the image restoration as the core technology of image processing, many studies are being progressed. In this paper, in order to restore the damaged image in the Salt and Pepper noisy environment, a modified adaptive switching median filter where the size of local mask can be varied according to the noise density was proposed. And using the PSNR as the standard for objective decision making of the improvement effect, it was compared with the existing methods.

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Edge Detection Method using Modified Coefficient Masks (변형된 계수 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Chung, Suk-Moon;Kim, Nam-Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.218-223
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    • 2013
  • The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

Crack segmentation in high-resolution images using cascaded deep convolutional neural networks and Bayesian data fusion

  • Tang, Wen;Wu, Rih-Teng;Jahanshahi, Mohammad R.
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.221-235
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    • 2022
  • Manual inspection of steel box girders on long span bridges is time-consuming and labor-intensive. The quality of inspection relies on the subjective judgements of the inspectors. This study proposes an automated approach to detect and segment cracks in high-resolution images. An end-to-end cascaded framework is proposed to first detect the existence of cracks using a deep convolutional neural network (CNN) and then segment the crack using a modified U-Net encoder-decoder architecture. A Naïve Bayes data fusion scheme is proposed to reduce the false positives and false negatives effectively. To generate the binary crack mask, first, the original images are divided into 448 × 448 overlapping image patches where these image patches are classified as cracks versus non-cracks using a deep CNN. Next, a modified U-Net is trained from scratch using only the crack patches for segmentation. A customized loss function that consists of binary cross entropy loss and the Dice loss is introduced to enhance the segmentation performance. Additionally, a Naïve Bayes fusion strategy is employed to integrate the crack score maps from different overlapping crack patches and to decide whether a pixel is crack or not. Comprehensive experiments have demonstrated that the proposed approach achieves an 81.71% mean intersection over union (mIoU) score across 5 different training/test splits, which is 7.29% higher than the baseline reference implemented with the original U-Net.

Noise Removal Filter Algorithm using Spatial Weight in AWGN Environment (AWGN 환경에서 공간 가중치를 이용한 잡음 제거 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.207-209
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    • 2021
  • In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

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Synthesis of Ketoconazole Derivatives

  • Ryu, Jae-Chun;Lee, Kwang-Jae;Lee, Sang-Hee
    • Bulletin of the Korean Chemical Society
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    • v.24 no.4
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    • pp.460-466
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    • 2003
  • For the drug master file (DMF) of ketoconazole, four impurities (1-4) contained in ketoconazole were synthesized. During the synthesis of 2, a new synthetic method of 1,4-dihydropyrazine was established. To oxidize the aminoalcohol (2j) to the aminal (2j-1), the standard Swern oxidation condition was modified to mask the nucleophilicity of the amino group temporarily using one equivalent of acetic acid. Derivative 3 was synthesized via regioselective bromination at the 2 position of the 4-aminophenol derivative (3a) using $Br_2$ in the presence of p-TsOH. The etherification of aryl bromide with the phenol derivative (1f) was accomplished by a modification of the general Cu-mediated reaction condition using excess 1f itself as a solvent at elevated temperature (190 ℃).

A Study on the Combustion Performance by the Improvement of In Cylinder Flow Motion in the Natural Gas Engine (실린더내 흡기유동개선이 천연가스엔진의 연소성능에 미치는 영향 연구)

  • Jeong, D.S.;Suh, S.W.;Oh, S.M.;Uhm, J.H.;Chang, Y.J.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.3 no.3
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    • pp.90-96
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    • 1995
  • In general, natural gas engine converted from gasoline engine has disadvantage of power decrease. In order to increase power output in natural gas engine, the improvement of in-cylinder flow motion has been believed as the most effective method. In this study, the geometry of combustion chamber in 4 valve DOHC natural gas engine is modified, and in-cylinder flow patterns is analyized. Also engine performance is evaluated according to the modification of in-cylinder flow motion.

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