• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.157-162
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• 2010

In this paper we propose a fractal analysis based on the discrete wavelet transform. It is well known that Fourier Transform is widely used for frequency analysis of random signal. However, the frequency domain is not used for expressing the sudden signal change and non-stationary signal at the time-axis by this method. Maximum value in the wavelet modules can be expressed by the Lipschitz exponent, which is useful to represent the characteristics of signal or the edge of an image. It is possible to reconstruct the original image only by using the few maximum points. The v possible image It iusing oil was acquired to interpret the maximum value. ufter that, it was applied to the v possible image of a ship model. In addition, the fractal dimens by by the conlapse process of the sediment particle was examined. In this paper, the fractal dimens by has been obtained by the maximum value and the experiment obtained from the visualized image also acquired the same result as existing methods.

• Journal of Fashion Business
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• v.9 no.5
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• pp.77-95
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• 2005

This study was for applying web based street fashion design analysis system(web-SFAS), which was designed in preceding research and realized, to a practical use. Web-SFAS was developed to analyze data fast, accurately, conveniently, and to provide them to related fields by using Information Technology (IT) in fashion design industry. By inputting, sorting and analyzing actual image data into this system, it purposes to check if it needs to be corrected and to verify its operation and application. This study was collected in 2004 s/s 177 points image data and survey results input to the system This system analyzed the results as follow ; First, in all four areas of S/S, many people wear soft materials and plain T-shirts on top and tough material and plain jeans on the bottom. Second, In the case of dresses, in many areas people wear tough fabric plain A-line, one-piece dresses but in Hapsung-dong, many people wear geometrical figures. Third, fashion image, most people wear a sportive casual style with semi casual in a close second. Therefore, web-SFAS can be useful system analyzing for the trendy apparel type, design, material, color, image and variable in demography through street fashion image data.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.148-154
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• 2009

In recent days, large-sized flat-panel display (FPD) has been increasingly applied to computer monitors and TVs. Mura defects, appearing as low contrast or non-uniform brightness region, sometimes occur in manufacturing of the Thin-Film Transistor Liquid-Crystal Displays (TFT-LCD). Implementation of automatic Mura inspection methods is necessary for TFT-LCD production. Various existing Mura detection methods based on regression diagnostics, surface fitting and data transformation have been presented with good performance. This paper proposes an efficient Mura detection method that is based on a regression diagnostics using studentized residuals for automatic Mura inspection of FPD. The input image is estimated by a linear model and then the studentized residuals are calculated for filtering Mura regions. After image dilation, the proposed threshold is determined for detecting the non-uniform brightness region in TFT-LCD by means of monitoring the every pixel in the image. The experimental results obtained from several test images are used to illustrate the effectiveness and efficiency of the proposed method for Mura detection.

• Fashion & Textile Research Journal
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• v.9 no.5
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• pp.472-477
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• 2007

This study was intended to identify the constructing factors and hierarchy of images in the gathered skirts, which is expected to be helpful in shape classification. The gathered skirts were made by different gathering conditions: three kinds of the gathers ratio(1.5T, 2.0T, 2.5T) and different fabrics(cotton, mixed wool, polyester). 45 undergraduate and graduate women students responded to the nine gathered skirts during December in 2004 to February in 2005. 184 words expressing gathered skirt were collected through the investigation and analysis of questionnaires. 32 words arranged in based on the standard form with frequency before conducting factor analysis to identify the constructing factors of gathered skirt images. As a result of factors analysis, 2 factors-H shape, A shape were found out as constructing factors of gathered skirts. To explain the hierarchy of gathered skirt images, cluster analysis was applied. To observe the association of 32 words, dendrogram was introduced, and to interpret the result, five sub clusters were determined. This 5 clusters were continuously combined according to their frequency, based on the factors marks. Two major division of image clusters were 'simple and neat image', and 'fairly good and feminine image'.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.626-633
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• 2003

Theoretical analysis of the depth measurement system with the use of a single camera and a rotating mirror has been done. A camera in front of a rotating mirror acquires a sequence of reflected images, from which depth information is extracted. For an object point at a longer distance, the corresponding pixel in the sequence of images moves at a higher speed. Depth measurement based on such pixel movement is investigated. Since the mirror rotates along an axis that is in parallel with the vertical axis of the image plane, the image of an object will only move horizontally. This eases the task of finding corresponding image points. In this paper, the principle of the depth measurement-based on the relation of the pixel movement speed and the depth of objects have been investigated. Also, necessary mathematics to implement the technique is derived and presented. The factors affecting the measurement precision have been studied. Analysis shows that the measurement error increases with the increase of depth. The rotational angle of the mirror between two image-takings also affects the measurement precision. Experimental results using the real camera-mirror setup are reported.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.669-672
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• 1998

In this paper, w epropose a fast fractal coding method based on correlation coefficients of subblocks in input image. In the proposed method, domain pool is selected based on correlation analysis of input image and the isometry transform for each block is chosen based on the IFS method. To investigate the performance of the proposed method, we compared image quality and encoding time with full search PIFS method and jacquin's PIFS method. Experimental results show that proposed method yields nearly the same performance in PSNR, and its encoding time is reduced for images size of 512*512 compared with full search PIFS method and jacquin's PIFS method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.587-594
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• 2005

In this paper, a robust correlation-based video tracking is proposed to track a moving object in correlated image sequences. A correlation-based video tracking algorithm seeks to align the incoming target image with the reference target block image, but has critical problems, so called a false-peak problem and a drift phenomenon (correlator walk-off. The false-peak problem is generally caused by highly correlated background pixels with similar intensity of a moving target and the drift phenomenon occurs when tracking errors accumulate from frame to frame because of the nature of the correlation process. At first, the false-peaks problem for the ordinary correlation-based video tracking is investigated using a simple mathematical analysis. And, we will suggest a robust selective-attention correlation measure with a gradient preprocessor combined by a drift removal compensator to overcome the walk-off problem. The drift compensator adaptively controls the template block size according to the target size of interest. The robustness of the proposed method for practical application is demonstrated by simulating two real-image sequences.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.248-250
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• 2003

An automatic approach and strategy for extracting building information from aerial images using combined image analysis and interpretation techniques is described in this paper. A dense DSM is obtained by stereo image matching. Multi-band classification, DSM, texture segmentation and Normalised Difference Vegetation Index (NDVI) are used to reveal building interest areas. Then, based on the derived approximate building areas, a shape modelling algorithm based on the level set formulation of curve and surface motion has been used to precisely delineate the building boundaries. Data fusion, based on the Dempster-Shafer technique, is used to interpret simultaneously knowledge from several data sources of the same region, to find the intersection of propositions on extracted information derived from several datasets, together with their associated probabilities. A number of test areas, which include buildings with different sizes, shape and roof colour have been investigated. The tests are encouraging and demonstrate that the system is effective for building extraction, and the determination of more accurate elevations of the terrain surface.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.889-898
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• 1997

Most general content-based image retrieval techniques use color and texture as retrieval indices. Spatial information is not used to color histogram and color pair based on color retrieval techniques. This paper proposes the selection of a set of representative in the duplicated color histogram, the analysis of spatial information of the selected colors and the image retrieval process based on the duplicated color histogram and spatial information. Two color historgrams for background and object are used in order to decide on color selection in the duplicated color histogram. Spatial information is obtained using a maximum entropy discretization. A retrieval process applies to duplicated color histogram and spatial to retrieve input images and relevant images. As the result of experiment of the image retrieval, improved color his togram and spatial information method hs increased the retrieval effectiveness more the color histogram method and color pair method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.