• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.358-363
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• 2009

Text region detection from the natural scene images used in a variety of applications, many research are needed in this field. Recent research methods is to detect the text region using various algorithm which it is combination of edge based and connected component based. Therefore, this paper proposes an text region detection using edge and regional minima/maxima transformation algorithm from natural scene images, and then detect the connected components of edge and regional minima/maxima, labeling edge and regional minima/maxima connected components. Analysis the labeled regions and then detect a text candidate regions, each of detected text candidates combined and create a single text candidate image, Final text region validated by comparing the similarity and adjacency of individual characters, and then as the final text regions are detected. As the results of experiments, proposed algorithm improved the correctness of text regions detection using combined edge and regional minima/maxima connected components detection methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.130-136
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• 2017

Recently, as demand of video processor unit rapidly increases, excellent quality of the video has been required. However, generally, video data occurs the quick flame of video due to various external causes in process of acquisition, treatment, and transmission, and major cause of the quick flame of the video is known as the noise. There are various kinds of noise, which are added to the video, AWGN is a typical one. Thus, this thesis suggested algorithm that treats in three methods by scale of the edge through using edge information of local masks. In case that edge pixel is big, it applied spatial weighting according to equation of straight line about direction of edge pixel. In case that edge pixel is middle, it suggested algorithm with spatial weighting filter and average filter, and for the smooth territory, it suggested algorithm that treats with average filter.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.209-215
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• 2020

In this paper, we propose an algorithm for segmenting weld bead images using edge enhancement and active contours. In the proposed method, high-frequency filtering and contrast improvement are performed for edge enhancement, and then, by applying the active contour method, only the weld bead region can be obtained. The proposed algorithm detects an edge through high-frequency filtering and reinforces the detected edge by using contrast enhancement. After the edge information is improved in this way, the weld bead area can be extracted by applying the active contour method. The proposed algorithm shows better performance than the existing methods for segmenting the weld bead in the image. For the objective reliability of the proposed algorithm, it was compared with the existing high pass filtering methods, and it was confirmed that the welding bead segmentation of the proposed method is excellent. The proposed method can be usefully used in evaluating the quality of the weld bead through an additional procedure for the segmented weld bead.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.625-630
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• 2016

Recently, various types of image contents are being produced, and interest in copyright protection technology is increasing. In this paper, we propose an image encryption technology for color images. This technique divides the image into RGB color components and then performs quad-tree decomposition based on the edge of image. After the quad-tree partitioning, encryption is performed on the selected blocks. Encryption is performed on color components to measure encryption efficiency, and encryption efficiency is measured even after reconstitution into a color image. The encryption efficiency uses a visual measurement method and an objective image quality evaluation method. The PSNR values were measured as 7~10 dB for color difference components and 16~19 dB for color images. The proposed image encryption technology will be used to protect copyright of various digital image contents in the future.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.2
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• pp.45-59
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• 1998

Halftonig is a technique to create the appearance of intermideate tone levels by controlling the spatial distribution of the binary pixel values. Recently, many printing devices such as image setter, inkjet printer, laser printer and facsimile, generate image, they require the technique. Ordered dither is achieved comparing the gray scale image to periodic array. This method is fast, but it occurs periodic patterns. Conentional error diffusion generates a good image. But processing speed is very slow and appeares worm artifacts in middle tone scale. To improve it, Bns(Blue noise Screen) is developed based on Gaussian distribution. In this paper, we discribe methods to design BNS based human visual characteristics and to improve blue appearing at edge area of image by USM(using unsharp mask).

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.479-486
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• 2016

In this paper, the algorithm which can convert a 2D image into a 3D Model will be discussed. The 2D picture drawn by a user is scanned for image processing. The Canny algorithm is employed to find the contour. The waterfront algorithm is proposed to find foreground image area. The foreground area is segmented to decompose the complex shapes into simple shapes. Then, simple segmented foreground image is converted into 3D model to become a complex 3D model. The 3D conversion formular used in this paper is also discussed. The generated 3D model data will be useful for 3D animation and other 3D contents creation.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.349-353
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• 2015

The conventional intensity histogram does not indicate edge information, which is important in the perception of image contrast. In this paper, we propose a multi-cue histogram (MCH) to represent a collaborative distribution of both the intensity and the edges of an image. Based on the MCH, if the intensity values have high frequency and a large gradient magnitude, they are spread into a larger dynamic range. Otherwise, the intensity values are not strongly stretched. As a result, image details, such as edges and textures, can be enhanced while artifacts and noise can be prevented, as demonstrated in the experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.210-216
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• 2010

In this study, we propose a novel method to segment an individual tooth region in a true color image. The difference of the intensity in RGB is initially extracted and subsequent morphological reconstruction is applied to minimize the spurious segmentation regions. Multiple seeds in the tooth regions are chosen by searching regional minima and a Sobel-mask edge operations is performed to apply MCWA(Marker-Controlled Watershed Algorithm). As the results of applying MCWA transform for our proposed tooth segmentation algorithm, the individual tooth region can be resolved in a CCD tooth color image.