• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3642-3667
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• 2021

Texture synthesis technology has the advantages of repairing texture and structure at the same time. However, during the filling process, the size of the patch is fixed, and the content of the filling is not fully considered. In order to be able to adaptively change the patch size, we used the exemplar-based inpainting technique as the test algorithm, considering the image structure and texture, calculated the image structure patch size and texture patch size, and comprehensively determined the image patch size. This can adaptively change the patch size according to the filling content. In addition, we use multi-layer images to calculate the priority, so that the order of image repair was more stable. The proposed repair algorithm is compared with other image repair algorithms. The experimental results showed that the proposed adaptive image repair algorithm can better repair the texture and structure of the image, which proved the effectiveness of the proposed algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.519-521
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• 1999

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.88-94
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• 2022

The relationship between sound and vision was experimentally confirmed by physicist Ernst Florens Friedrich Chladni as early as the 18th century and formally entered into systematic research. With the development of emerging media technology, sound reactive type visual content is not limited to a single visual interaction based on the vibration of sound, and its visual content shows a diversified and scalable development trend according to different purposes in many fields. This study analyzes the development and changes of sound visual art contents from early stage to modernization, and analyzes the development characteristic of sound visual art content in different fields and scene environments influence by interactive media, new media technologies and devices by means of case analysis. Through this research, it is expected that the sound reactive type visual art content can continue to develop and extend in the existing fields, while explore the scalability of the application of sound reactive type visual art content in more fields.

• Journal of the Korean Society of Costume
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• v.62 no.4
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• pp.58-68
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• 2012

Personal image concerns a person's talent, expertise, as well as the internal and external image. It is a core value that differentiates one individual from another. As personal branding via personal image management has become more important, there is a fast-growing number of online systems that provide self-test programs to analyze one's style and habits and also provide expert advice for not only styles but lifestyles as well. This study develops a systematic and objective personal image consulting system and offers basic information for the research of personal image making. For that purpose, the study attempts to examine the present state of global companies that use online image consulting programs and analyze their digital content. The results are as follows: 1) two domestic companies, Colorz and Atzine, and seven foreign companies, notably Covet and Boutique, were brisk in business; 2) two types of personal image-diagnosis programs - Visual search and Virtual matching - are now in operation; and 3) mobile applications exist as an evolved personal image-diagnosis program. With an increased interest in such programs, various companies at home and abroad are establishing systematic and scientific analysis systems, which are needed for personal image-making online. Under these circumstances, domestic companies are also urged to enhance levels of image-diagnosis content and actual commercialization and utilization, to develop programs that enable objectified, systematic personal image-making. To this end, the results of this study may serve as a helpful tool to consider future directions.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.21-27
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• 2019

The study empirically analyzed the effects of content attitudes and recall on digital signage advertising appeal (information appeal vs. image appeal) and interactivity level (low vs. high). As a result, first, it was found that a moderately low level of interactivity had a positive effect on content attitudes and recall than when the level of digital signage was extremely high. In addition, at moderately low levels of interactivity, information appeals had higher content attitudes and recalls than image appeals. Second, the content of image appeal has a positive effect on attitude when the digital signage level of interactivity is high, and the image recall ad and information appeal ad have negative effects on recall. Third, the low level of interactivity of digital signage has a positive effect on the content attitude and recall of information appeal. With the advent of digital media in recent years, concerns about how to construct the level of interactivity and information content on a strategic level are increasing in practice. The results of this study are expected to suggest the direction of the strategic grounds for this.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.1-10
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• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• ETRI Journal
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• v.36 no.5
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• pp.791-798
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• 2014

As a new hybrid broadcasting service, augmented broadcasting shows enhanced broadcasting content on a large TV screen, while augmented reality (AR) on a mobile device augments additional graphical content onto an input image from the device's own camera to provide useful and convenient information for users. A one-sided broadcasting service using AR has already been attempted in virtual advertisements during sport broadcasts. However, because its augmentation is preprocessed before the video image is transmitted, the viewer at home may have no influence on this formation; and no interaction for the user is possible unless the viewer has a direct connection to the content provider. Augmented broadcasting technology enables viewers to watch mixed broadcasting content only when they want such service and to watch original broadcasting content when they do not. To realize an augmented broadcasting service, the most important issue is to resolve the hybrid content synchronization over heterogeneous broadcast and broadband networks. This paper proposes a novel hybrid content synchronization scheme for an augmented broadcasting service and presents its implementation and results in a terrestrial DTV environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1071-1092
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• 2014

Annotating images with tags that describe the content of the images facilitates image retrieval. However, this task is challenging for both humans and computers. In response, a new approach has been proposed that converts the manual image annotation task into CAPTCHA challenges. However, this approach has not been widely used because of its weak security and the fact that it can be applied only to annotate for a specific type of attribute clearly separated into mutually exclusive categories (e.g., gender). In this paper, we propose a novel image annotation CAPTCHA scheme, which can successfully differentiate between humans and computers, annotate image content difficult to separate into mutually exclusive categories, and generate verified test images difficult for computers to identify but easy for humans. To test its feasibility, we applied our scheme to annotate images of human faces with their age groups and conducted user studies. The results showed that our proposed system, called AgeCAPTCHA, annotated images of human faces with high reliability, yet the process was completed by the subjects quickly and accurately enough for practical use. As a result, we have not only verified the effectiveness of our scheme but also increased the applicability of image annotation CAPTCHAs.

• ETRI Journal
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• v.42 no.1
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• pp.67-77
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• 2020

Image captioning has received significant interest in recent years, and notable results have been achieved. Most previous approaches have focused on generating visual descriptions from images, whereas a few approaches have exploited visual descriptions for image classification. This study demonstrates that a good performance can be achieved for both description generation and image classification through an end-to-end joint learning approach with a loss function, which encourages each task to reach a consensus. When given images and visual descriptions, the proposed model learns a multimodal intermediate embedding, which can represent both the textual and visual characteristics of an object. The performance can be improved for both tasks by sharing the multimodal embedding. Through a novel loss function based on class activation mapping, which localizes the discriminative image region of a model, we achieve a higher score when the captioning and classification model reaches a consensus on the key parts of the object. Using the proposed model, we established a substantially improved performance for each task on the UCSD Birds and Oxford Flowers datasets.