• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.550-558
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• 2013

The infrared and visible images are represented by different information due to the different wavelength of the light. The infrared image has thermal information and the visible image has texture information. Desirable results are obtained by fusing infrared and visible information. To enhance a visible image, we extract a weight map from a visible image using saturation, brightness. After that, the weight map is adjusted using thermal information in the infrared image. Finally, an enhanced image is resulted from combining an infrared image and a visible image. Our experiment results show that our proposed algorithm is working well to enhance the smoke in the original image.

• The Research Journal of the Costume Culture
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• v.21 no.4
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• pp.546-561
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• 2013

This study investigated how consumers perceive brand image, the consistency between the images of parent brands and extended brands, the consistency of their advertising images, the differences between brand image and advertising image, and how consumers' brand attitudes change based on those differences. An online survey was administered to women in their 20s and 30s who often use cosmetics and are interested in brands. The brands considered in this research were Chanel, Dior, Armani, and Anna Sui, which have extended brands in the clothing and cosmetics areas. In terms of consumers' perception of brand image, it was found that clothing and cosmetic brands were perceived similarly. In addition, significant differences were found in consumers' preferences and purchase intentions of clothing and cosmetic brands, and those whose perceptions of brand image did not change or increased after looking at advertising images had more positive brand attitudes than the group of people who had higher perception of brand image before looking at advertising images. Therefore, in terms of brand extension, it was revealed that the image of a parent brand affected an extended brand, and that the higher was consumers' recognition of brand image through advertising, the more positive was their attitude toward the brand.

• Fashion & Textile Research Journal
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• v.12 no.5
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• pp.626-632
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• 2010

The results of the image evaluations by various shapes of skirts which are typical female's lower garment were as follows; 1. The composition factors of images by the shapes of skirts were classified into five factors. The 1st factor is lovely image factor, the 2nd is attractive image factor, the 3rd is practical image factor, the 4th is slim-looking image factor and the 5th is long-looking image factor. 2. In the 1st factor- lovely image factor, tiered skirt, $360^{\circ}$ flared skirt and $180^{\circ}$ flared skirt were evaluated to express lovely images. In the 2nd factor- attractive image factor, $180^{\circ}$ flared skirt was evaluated to express refine and attractive images. In the 3rd factor- practical image factor, $360^{\circ}$ flared skirt and gathered skirt were evaluated to express easy and practical images. In the 4th factor- slim looking image factor, males evaluated 8gored skirt and females evaluated gathered skirt to express fat images. In the 5th factor- long looking image, $180^{\circ}$ flared skirt was evaluated to express long looking images by both sexes. 3. In the lovely image factor, gathered skirt was evaluated most differently between the sexes. Both in the attractive and practical image factor, tiered skirt was evaluated most differently between the sexes. 4. In the preference of male and female university students according to the shapes of skirts, both the sexes prefered flared skirt. But the low prefered shapes of skirts were differently evaluated between the sexes; the male students' was A-lined skirt and the female's was pleated skirt and wrap skirt.

• Korean Journal of Human Ecology
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• v.15 no.6
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• pp.1049-1062
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• 2006

The purpose of this study is to find out the image according to formative properties of hat and garment in the fashion collection. For the study, the 96 stimuli found frequently in fashion collection from the S/S season of 1998 to the F/W season of 2004 were selected. Sets of stimulus and response scales (7 point semantic) were used as experimental materials. The stimuli were 96 pictures with the types of hat(4), the lengths of hair(3), the types of garment(3), the relations between the color of garment and hat(4), and the materials(4) and patterns of garment(2). The subjects were 415 women college students majoring fashion design related fields and living in Seoul and Gyeongsangnam-do. As statistical methods for data analysis, Factor Analysis, ANOVA test, and LSD test were used. The items of the adjectives were classified into 5 image dimensions; attractiveness, gracefulness, concentration, cuteness, and hardness and softness. Among these factors, each dimensional image was affected by formative properties of hat and garment. The image of a hat-wearer was perceived differently according to the hair style and the formative properties of hat and garment even if the type of hat was same.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.91-102
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• 2020

Recently, generative adversarial networks (GANs) is a field of research that has rapidly emerged wherein many studies conducted shows overwhelming results. Initially, this was at the level of imitating the training dataset. However, the GAN is currently useful in many fields, such as transformation of data categories, restoration of erased parts of images, copying facial expressions of humans, and creation of artworks depicting a dead painter's style. Although many outstanding research achievements have been attracting attention recently, GANs have encountered many challenges. First, they require a large memory facility for research. Second, there are still technical limitations in processing high-resolution images over 4K. Third, many GAN learning methods have a problem of instability in the training stage. However, recent research results show images that are difficult to distinguish whether they are real or fake, even with the naked eye, and the resolution of 4K and above is being developed. With the increase in image quality and resolution, many applications in the field of design and image and video editing are now available, including those that draw a photorealistic image as a simple sketch or easily modify unnecessary parts of an image or a video. In this paper, we discuss how GANs started, including the base architecture and latest technologies of GANs used in high-resolution, high-quality image creation, image and video editing, style translation, content transfer, and technology.

• International Journal of Contents
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• v.13 no.4
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• pp.70-79
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• 2017

Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.339-342
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• 2017

Geometric transform of an image is used to image correction. Ridid-Body, Simlilary transform, etc, many correction methods are exist in computer vision. Image warping is used to correction for image with perspective. To image warping I extracted 4 feature point about warping position. But It is difficult to extract 4 points accurately and warping result with these point is occurs error over 3 or 4 pixel at warping position. So I used template matching to extract 4 points correctly and selected repeatedly 2 points of 4 points because to confirm result correctly. positions of 2 points are changed in near of 3 by 3 pixel and warped each change. So I selected optimal 4 points with a error of less than 1 pixel and finally, warped image using optimal points. For this way is possible to obtain optimum result.

• Journal of IKEEE
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• v.23 no.4
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• pp.1465-1468
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• 2019

The image noise improvement algorithm proposed in this paper extracts the boundary line by using the window of the binarized image to detect the gesture motion. Boundary line blurring is prevented by improving Gaussian noise generated during video output. To improve gesture recognition in low-light environments, an image noise enhancement algorithm has been designed to provide an output image close to the base image. Analyzing the experimental results, we found almost 10% improvement in the results compared to the results of the existing Median filter.

• Current Optics and Photonics
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• v.2 no.4
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• pp.315-323
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• 2018

A new multiple-image encryption scheme that is based on a compressive ghost imaging concept along with a Fourier transform sampling principle has been proposed. This further improves the security of the scheme. The scheme adopts a Fourier transform to sample the original multiple-image information respectively, utilizing the centrosymmetric conjugation property of the spatial spectrum of the images to obtain each Fourier coefficient in the most abundant spatial frequency band. Based on this sampling principle, the multiple images to be encrypted are grouped into a combined image, and then the compressive ghost imaging algorithm is used to improve the security, which reduces the amount of information transmission and improves the information transmission rate. Due to the presence of the compressive sensing algorithm, the scheme improves the accuracy of image reconstruction.