• Journal of Information Processing Systems
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• v.5 no.1
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• pp.1-4
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• 2009

Level set methods are the numerical techniques for tracking interfaces and shapes. They have been successfully used in image segmentation. A new variational level set evolving algorithm without re-initialization is presented in this paper. It consists of an internal energy term that penalizes deviations of the level set function from a signed distance function, and an external energy term that drives the motion of the zero level set toward the desired image feature. This algorithm can be easily implemented using a simple finite difference scheme. Meanwhile, not only can the initial contour can be shown anywhere in the image, but the interior contours can also be automatically detected.

• Journal of Fashion Business
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• v.22 no.4
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• pp.130-144
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• 2018

This study aims to examine the future image of the fashion industry according to the level of consumer knowledge and anxiety about the 4th industrial revolution. An online survey was carried out from March 13 to 23, 2018. A total of 698 consumers participated in the survey. The results of the study are as follows. The consumer knowledge level about the 4th industrial revolution was 10.2% for the first recognition, 48.3% for the term recognition, and 41.5% for the content understanding. The level of consumer anxiety about the 4th industrial revolution was 36.5% lower than average and 63.5% higher than the average. An ANOVA was conducted to confirm the anxiety according to the knowledge level of the 4th industrial revolution. The results revealed that consumers with higher knowledge level felt more anxiety than consumers with a lower level of knowledge. Consumer's knowledge level about the 4th industrial revolution did not affect the future image of fashion industry and individual phases of the fashion industry. Consumer's anxiety level about the 4th industrial revolution had a partial influence on the future image of the fashion industry and on each phase of the fashion industry. In the midstream and downstream areas of the fashion industry, significant differences were observed in the future image according to the level of anxiety.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.

• Journal of the Korean Society of Costume
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• v.31
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• pp.223-236
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• 1997

The purpose of this study is to set up the concept and the structure of 'the image' theoretically. The study is carried out by the literature research. The image is constituted of several concepts which are as followed: The concept of definition: perception cognition/impression. The concept of target: objective/per-son The concept of content: internal/exter-nal The concept of level :lower/upper Especially levels of image are divided into 3 different levels which are 'simple level' 'complex level 1' 'com-plex level 2' The concept of image is classified into the horizontal and the vertical structure. The concepts of the definition the target the con-tent are included in horizontal strcture and the concept of the level is included in the ver-tical structure.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.143-148
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• 2022

This paper attempted to analyze the correlation between the risk image of the evacuees in the tunnel and the variables that affect the evacuation behavior due to the closed feeling. As to whether there is a difference in the level of recognizing the tunnel risk image according to the distribution of jobs, the null hypothesis was rejected at the significance probability of 0.002, so it can be said that the level of recognition of the tunnel risk image varies depending on the job group. In the distribution difference between gender and tunnel risk image recognition level, the significance probability was 0.012, indicating that the null hypothesis was rejected, indicating that the tunnel risk recognition distribution according to gender was different. As a result of analyzing the distribution difference between the tunnel's closed feeling and the tunnel risk perception level, the significance probability was 0.001, and the null hypothesis was rejected, indicating that there was a difference in the tunnel risk image level.

• Journal of Korea Multimedia Society
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• v.15 no.12
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• pp.1417-1429
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• 2012

In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.699-706
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• 2007

This article is an approach to improving the clustering of Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering algorithm, a self-organizing map (SOM) proposed by Kohonen is used. To evaluate the clustering efficiencies of SOMs, we propose a simple but effective measure indicating the accumulativeness of same class images and the perplexities of class distributions. Our approach is to advance the existing measures through defining and using new measures accumulativeness on the most superior clustering node and concentricity to evaluate clustering efficiencies of SOMs. The experimental results show that the high-level text features are more useful in SOM-based Web image clustering.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.72-79
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• 1995

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurment of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easily illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is 0 in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed automatic inspection system can be applied in real situation.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• Journal of Families and Better Life
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• v.27 no.4
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• pp.67-80
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• 2009

Most consumers prefer certain brand logos of cosmetics in accordance with their cognized brand image and self image. In other words, consumers select particular brands from various brands in the market based on their image. The purpose of this study is to find out which factors affect a consumer's attention of cosmetic brand logos. The brand logo that has an abstractive image, sign, and brand pursues the consumer who purchases the cosmetic product and image. The semistic analytic method of pierce was used. The major findings are as follow. 1) The image of the logo of a female consumer is a significant difference in the educational level variable. The result compares, according to marital status and educational level, the traditional characteristic from the logo of the image. 2) There is a significant difference in the logo type. It follows the educational level variable in female consumers. The result compares a preference by inserting a picture in the logo. A high preference appears based on age, marital status, occupation, and income. 3) There are significant differences in demographics school register with attitude of the logo. It follows the attitude that appeared about in age. Finally, when examining closely the effects between cosmetics' brand logo and logo's implications, there are significant differences in the income level, educational level, age, and marital status. The feminine consumer tends to prefer accordance between the cosmetics brand logo and the logo's implications.