• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.332-333
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• 2021

In this paper, we propose a new image classification method based on several trainings, which is mainly used to solve model overfitting and non-convergence in image classification tasks of small data sets and to improve classification accuracy.

• The Research Journal of the Costume Culture
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• v.15 no.2 s.67
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• pp.311-325
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• 2007

The purpose of this study is to investigate the effect of eyeshadow color(brown, purple), lipstick color(red, red purple, and yellow red), and lipstick tone(vivid, light, dull, and dark), clothing style(formal, casual), clothing tone(N9, N7, N4, N2) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 128 color pictures manipulated with the combination of eyeshadow color, lipstick color, lipstick tone, clothing style, and clothing tone using computer simulation. The subjects were 768 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 5 different components, attractiveness, stability, cuteness, visibility, and tenderness. In the 5 image components, clothing style and clothing tone showed independent effect. In the stability, cuteness and visibility, lipstick color showed independent effect. Eyeshadow color and lipstick tone influenced independently on the attractiveness, stability and visibility. In the coordination of achromatic clothing with makeup face, attractiveness image by the coordination of lipstick tone with clothing tone, cuteness image by the coordination of lipstick tone with clothing style or clothing style with clothing tone, visibility image can be produced by the coordination of eyeshadow color with lipstick color.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6017-6037
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• 2017

In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

• Journal of the Korea Fashion and Costume Design Association
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• v.11 no.1
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• pp.111-121
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• 2009

The purpose of this study is to investigate the effect of body type(thin, standard, fat), necktie width(narrow, medium, wide), gender(man, woman) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 9 color pictures manipulated with the combination of necktie-width and body type using computer simulation. The subjects were 116 male undergraduates and 99 female undergraduates living in Gyeongsangnam-do. Image factor of the stimulus was composed of 4 different components, young-activity, attractiveness-gracefulness, stability, and boldness. In the young-activity, attractiveness-gracefulness and stability, body type and necktie-width showed independent effect. In the boldness, body type showed independent effect. Significant interaction effects of body type and necktie-width on young-activity, attractiveness-gracefulness and stability were found. For young-activity image, necktie of narrow width were effective. For attractiveness-gracefulness image, body type of standard were effective. For stability image, body type of standard and body type of thin on necktie of narrow and medium width were effective. The male fashion image can be perceived differently according to combination of the clues used in body type and necktie-width. Therefore, when the male fashion to create images that will have to consider the body type and necktie width.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1124-1132
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• 2009

We proposed a new method to improve the resolution of elemental image set in the integral imaging system using super-resolution image reconstruction method. Adjacent elemental images have same image region which is projected from the common area of object. These projected images in the elemental image can be used for low resolution images of super-resolution method. Two methods for resolution improvement of elemental image set using super-resolution method are proposed. One is super-resolution among the elemental image sets and the other is among the elemental images. Simulation results are compared with resolution improved elemental image set using interpolated method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Journal of Fashion Business
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• v.12 no.1
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• pp.30-44
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• 2008

The purpose of this study is to investigate the effect of eyeshadow color(brown, purple), lipstick color(red, red purple, and yellow red), and lipstick tone(vivid, light, dull, and dark), clothing tone(vivid, light, dull, and dark) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 64 color pictures manipulated with the combination of eyeshadow color, lipstick color, lipstick tone, and clothing tone using computer simulation. The subjects were 384 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 4 different components (attractiveness, visibility, gracefulness, and tenderness). In the 4 image components, eyeshadow color and clothing tone showed independent effect. Lipstick tone influenced independently on the visibility and tenderness. In the contrast color coordination of clothing and makeup, visibility image by the coordination of lipstick color with lipstick tone, lipstick color with clothing tone or lipstick tone with clothing tone, gracefulness image by the coordination of eyeshadow color with lipstick color, tenderness image can be produced by the coordination of eyeshadow color with lipstick color, eyeshadow color with lipstick tone or eyeshadow color with clothing tone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2527-2545
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• 2016

Measuring the similarity of given samples is a key problem of recognition, clustering, retrieval and related applications. A number of works, e.g. kernel method and metric learning, have been contributed to this problem. The challenge of similarity learning is to find a similarity robust to intra-class variance and simultaneously selective to inter-class characteristic. We observed that, the similarity measure can be improved if the data distribution and hidden semantic information are exploited in a more sophisticated way. In this paper, we propose a similarity learning approach for retrieval and recognition. The approach, termed as LDA-FEK, derives free energy kernel (FEK) from Latent Dirichlet Allocation (LDA). First, it trains LDA and constructs kernel using the parameters and variables of the trained model. Then, the unknown kernel parameters are learned by a discriminative learning approach. The main contributions of the proposed method are twofold: (1) the method is computationally efficient and scalable since the parameters in kernel are determined in a staged way; (2) the method exploits data distribution and semantic level hidden information by means of LDA. To evaluate the performance of LDA-FEK, we apply it for image retrieval over two data sets and for text categorization on four popular data sets. The results show the competitive performance of our method.

• Spatial Information Research
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• v.12 no.1
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• pp.111-125
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• 2004

Improvements of classification accuracy are main issues in satellite image classification. Considering the facts that multiple images in the same area are available, there are needs on researches aiming improvements of classification accuracy using multiple data sets. In this study, orthogonal summation method of Dempster-Shafer theory (theory of evidence) is proposed as a multiple imagery classification method and posterior probabilities and classification uncertainty are used in calculation process. Accuracies of the proposed method are higher than conventional classification methods, maximum likelihood classification(MLC) of each data and MLC of merged data sets, which can be certified through statistical tests of mean difference.

• Convergence Security Journal
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• v.6 no.2
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• pp.53-60
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• 2006

In the applications such as CAD or image processing, a variety of geometric objects are manipulated. A polygon in which all the edges are parallel to x- or y-axis is decomposed into simple rectangles for efficient handling. But, depending on the partitioning algorithms, the same region can be decomposed into a completely different set of rectangles in the number, size and shape of rectangles. So, it is necessary an algorithm that compares two sets of rectangles extracted from two scenes such as CAD or image to see if they represent the same region. This paper proposes an efficient algorithm that compares two sets of rectangles. The proposed algorithm is not only simpler than the algorithm based on sweeping method, but also reduces the number $O(n^2)$ of overlapped rectangles from the algorithm based on a balanced binary tree to O(nlogn).