• The Research Journal of the Costume Culture
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• v.18 no.4
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• pp.640-654
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• 2010

The purpose of this study is to design neckties that are motivated by Christmas symbol images that have been known to public most widely in the basis of Day marketing so as to develop the competitive commodities closed to consumers' emotion in the fashion industry. As a method of this study were to use Adobe Illustrator CS2, which is one of the vector graphic programs, to present the motif design such as Santa Claus, trees, presents and letters among Christmas symbols, and are to apply to neckties by giving a change with striped pattern, all over pattern and one point pattern. The results are as follows; Firstly, Santa Claus image was expressed by color contrast with red and white, which was perceived by red, green and white that are mostly used in Christmas. Secondly, tree images are expressed abstractly with color contrast where red and green are contrasted, and color way change was given for symbol color of Christmas. Third, in the image of gift, the image of share and image of colorfulness were considered for expression by making motifs of three dimensional hexahedron shape. Fourthly, in the image of type, motif was expressed by giving a change in horizontal and vertical writing types.

• Child Health Nursing Research
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• v.7 no.3
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• pp.342-358
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• 2001

The purpose of the study is both to develope the group counseling program applying Reality Therapy, by which positive body image could be conceived by adolescent women, by helping them identify their bodies as what they are, and then admit their real bodies, and also find out some practical methodologies of self-esteem, and to verify the program to show how effectively this program can be applied to them. Data were collected by self-reported questionnaires(body image and depression) from 59 high school girls in Seoul who were selected by criteria of this study, from the 1st of September to 10th of November, 2000. The experimental group participated in the group counseling by applying Reality Therapy with 8 sessions for 4 weeks. Descriptive statistics, homogeneity test, hypothesis testing, reliability were performed statistically by utilizing SAS pc program, and additionally the reaction due to the change of body image by adolescent women was also analyzed. The results drawn through the present study are as follows: 1. A hypothesis that 'adolescent women who participated in the group counseling program by applying Reality Therapy may get higher points on body image than adolescent women who did not participated' has been adopted (t=6.73, p=.000). 2. A hypothesis that 'adolescent women who participated in the group counseling program by applying Reality Therapy may get lower points on depression than adolescent women who did not participated' has been adopted (t=5.28, p=.000). 3. After applying the group counseling program, the degree of depression for upper group who obtained higher preliminary points on depression has decreased rather meaningfully more than that for lower group who obtained higher preliminary points(t=5.58, p=.000). 4. Reactions associated with positive change in body image of adolescent women who participated in the group counseling program by applying Reality Therapy has been shown to be body acceptance, enhancement of self-esteem, and change of value judgment of beauty. 5. The difference in the motivation and attitude of each group has been observed, by analyzing the reactions obtained from those who show the highest change of body image and those who show the lowest change of body image through the group counseling program by applying Reality Therapy. According to the present studies, it can be concluded that the group counseling program by applying Reality Therapy has turned out as an effective strategy for nursing intervention for adolescent women, by helping them form positive body images and reducing depression.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2634-2636
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• 2001

This paper proposes a new method of retrieving images from large image databases. The method is based on VQ(Vector Quantization) of local texture information at interest points automatically detected in an image. The texture features are extracted by Gabor wavelet filter bank, and rearranged for rotation. These features are classified by VQ and then construct a pattern histogram. Retrievals are performed by just comparing pattern histograms between images. Experimental results have shown the robustness of the proposed method to image rotation, small scale change, noise addition and brightness change and also shown the possibility of the retrieval by a partial image.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.05a
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• pp.96-97
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• 2001

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.47-52
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• 2003

Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3712-3729
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• 2020

Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.239-246
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• 2010

Satellite image has capability of getting a broad data rapidly. It is possible that acquisition of change information about topography, land, ecosystem and urbanization etc. from multi-temporal satellite Images. In this study, the time-series change of vegetation has detected using four period Landsat Imageries. Also, NDVI was used to recognize the vitality of vegetation. Time series change of vegetation about study area was able to detect effectively by the results of classification and NDVI. It is expected that this study should be utilized as the decision making related to the effective management and plan establishment.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.271-285
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• 2009

Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.13-16
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• 2014

This study aims to examine the effects of watching 2D and 3D images on the blink rate. Regarding the image watch, their blink rate for 2D and 3D images was separately checked for 1 minute in the 1m distance, before the watch, after 15 minutes of watch, and after 30 minutes of watch. About the change of their blink rate in the 2D image watch, it tended to become higher than that before watching the image; however, there was no statistical significance (paired t-test, p=0.106, p=0.062). And in the 2D image watch, it tended to increase in comparison between after 15 minutes and after 30 minutes, but there was no statistical significance (paired t-test, p=0.623). Meanwhile, about the change of their blink rate in the 3D image watch, it tended to decrease statistically significantly both after 15 minutes and after 30 minutes when compared with that before watching the image (paired t-test, p=0.000, p=0.000). In the 3D image watch, it tended to increase in comparison between after 15 minutes and after 30 minutes; however, there was no statistical significance (paired t-test, p=0.867).