• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.257-262
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• 2020

This study recruited adults aged 35 to 64 living in Daegu and Gyeongsang buk-do to analyze the images of the elderly perceived by the mid and older- aged adults and their preparation for later life. The results of this study are as follows: First, as for the images of elderly people recognized by the research subjects, psychological images were the most positive, followed by physical and social images. Those with a higher education level, full-time job, and parents alive had more positive images of the elderly. The psychological images were better in those married compared to singles or divorcees, and the higher the age considered as elderly, the better the psychological and social images of the elderly. Second, preparation for later life in the mid and older-aged adults was better in order of emotional and physical preparation, whereas economic and leisure and social preparation were not enough. Those who are female, those with a higher education level, higher average monthly household income, professional job, and full-time job, and those who have an older age in mind as a definition of elderly have been better prepared for later life. Third, it was found that the sub-factors of their images of elderly people and preparation for later life affected each other, and the more positive their images of elderly people, the better they had been prepared for later in life. The results of this research suggests a desirable direction for improving the images of the elderly, implicating the necessity of exploring measures to provide individual and social support and developing educational programs for successful life after retirement.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.365-384
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• 2024

The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.4
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• pp.313-332
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• 2014

With the increased creation, distribution, and use of image in context of the development of digital technologies and internet, research endeavors have accumulated drastically. As two dominant aspects of image retrieval have been considered content-based and concept-based image retrieval, concept-based image retrieval has been focused in the field of Library and Information Science. This study aims to systematically review the accumulated research of image retrieval from the perspective of LIS field. In order to achieve the purpose of this study, two data sets were prepared: a total of 282 image retrieval research papers from Web of Science, and a total of 35 image retrieval research from DBpia in Kore for comparison. For data analysis, systematic review methodology was utilized with bibliographic analysis of individual research papers in the data sets. The findings of this study demonstrated that two sub-areas, image indexing and description and image needs and image behavior, were dominant. Among these sub-areas, the results indicated that there were emerging areas such as collective indexing, image retrieval in terms of multi-language and multi-culture environments, and affective indexing and use. For the user-centered image retrieval research, college and graduate students were found prominent user groups for research while specific user groups such as medical/health related users, artists, and museum users were found considerably. With the comparison with the distribution of sub-areas of image retrieval research in Korea, considerable similarities were found. The findings of this study expect to guide research directions and agenda for future.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.1-10
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• 2019

Object-based image matching algorithms have been widely used in the image processing and computer vision fields. A variety of applications based on image matching algorithms have been recently developed for object recognition, 3D modeling, video tracking, and biomedical informatics. One prominent example of image matching features is the Scale Invariant Feature Transform (SIFT) scheme. However many applications using the SIFT algorithm have implemented based on stand-alone basis, not client-server architecture. In this paper, We initially implemented based on client-server structure by using SIFT algorithms to identify and match objects in biomedical images to provide useful information to the user based on the recently released Mobile platform. The major methodological contribution of this work is leveraging the convenient user interface and ubiquitous Internet connection on Mobile device for interactive delineation, segmentation, representation, matching and retrieval of biomedical images. With these technologies, our paper showcased examples of performing reliable image matching from different views of an object in the applications of semantic image search for biomedical informatics.

• Journal of Platform Technology
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• v.12 no.1
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• pp.128-140
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• 2024

'Deepfake' refers to a video synthesis technique that utilizes various artificial intelligence technologies to create highly realistic fake content, causing serious confusion to individuals and society by being used for generating fake news, fraud, malicious impersonation, and more. To address this issue, there is a need for methods to detect malicious images generated by deepfake accurately. In this paper, we extract and analyze saliency features from deepfake and real images, and detect candidate synthesis regions on the images, and finally construct an automatic deepfake detection model by focusing on the extracted features. The proposed saliency feature-based model can be universally applied in situations where deepfake detection is required, such as synthesized images and videos. To demonstrate the performance of our approach, we conducted several experiments that have shown the effectiveness of the deepfake detection task.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.383-394
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• 2018

In this paper, we investigate image and video compression techniques based on deep learning which are actively studied recently. The deep learning based image compression technique inputs an image to be compressed in the deep neural network and extracts the latent vector recurrently or all at once and encodes it. In order to increase the image compression efficiency, the neural network is learned so that the encoded latent vector can be expressed with fewer bits while the quality of the reconstructed image is enhanced. These techniques can produce images of superior quality, especially at low bit rates compared to conventional image compression techniques. On the other hand, deep learning based video compression technology takes an approach to improve performance of the coding tools employed for existing video codecs rather than directly input and process the video to be compressed. The deep neural network technologies introduced in this paper replace the in-loop filter of the latest video codec or are used as an additional post-processing filter to improve the compression efficiency by improving the quality of the reconstructed image. Likewise, deep neural network techniques applied to intra prediction and encoding are used together with the existing intra prediction tool to improve the compression efficiency by increasing the prediction accuracy or adding a new intra coding process.

• Journal of IKEEE
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• v.18 no.4
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• pp.603-611
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• 2014

When image sensor and lens are fixed on the module, mechanical errors often induce tilt, rotation, or narrow field-of-view of the acquired image. Therefore, the optical characteristics of image sensor modules should be tested by test equipments. This paper explains how to test the optical characteristics of images sensors. It also proposes the standardized description methods of optical characteristics tests which are similar with those of image acquisition characteristics tests. The proposed method helps the test equipments to perform image acquisition characteristics tests and optical characteristics tests together.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.468-472
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• 2020

시각적 질의응답(Visual Question Answering, VQA)은 주어진 이미지에 연관된 다양한 질문에 대한 올바른 답변을 예측하는 기술이다. 해당 기술은 컴퓨터 비전-자연어 처리 연구분야에서 활발히 연구가 진행되고 있으며, 질문의 의도를 정확히 파악하고, 주어진 이미지에서 관련 단서 정보를 찾는 것이 중요하다. 또한, 서로 이질적인 특성을 지닌 정보(이미지 객체, 객체 위치, 질문)를 통합하는 과정도 중요하다. 본 논문은 질문의 의도에 알맞은 정보를 효율적으로 사용하기 위해 멀티 모달 입력 이미지 객체, 객체 위치, 질문)에 대한 Multi-modal Message Aggregation (MMA) 제안하며 이를 통해 한국어 시각적 질의응답 KVQA에서 다른 모델보다 더 좋은 성능을 확인하였다.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.69-79
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• 2015

The purpose of this study is to investigate the effect of national image, brand image, and country of origin on Chinese consumer's purchase attitude and purchase intention of Korean cosmetic products which applied a high and/or convergence technology. The survey was completed by chinese customers and the data is analysis with SPSS 21.0. The results show that national image, brand image, and country of origin image have a positive impact on Chinese consumer's purchase attitude and purchase intention. This results imply that when Korean companies enter into chinese markets, if they perform very aggressive promotion activities on national image, brand image, and country of origin image, they can be successful by transforming positively chinese consumer's purchase attitude and purchase intention of Korean products.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.324-326
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• 2021

증강현실은 현실 공간에 가상의 객체를 합성한 영상을 생성하는 기술이다. 증강현실 기술에 대한 지속적인 수요 증가와 기술 발전이 이루어져 왔으며, 앞으로 사용자에게 현실을 기반으로 생성된 이질감이 느껴지지 않는 정교한 영상을 제공할 수 있으리라 기대할 수 있다. 본 논문에서는 증강현실 기술로 생성된 합성 영상이 정교한 영상임을 판단할 수 있는 객관적인 기준을 마련하기 위해 기존의 머신 러닝 기반의 이미지 분류 모델들로 합성 이미지 예측에 대한 실험을 진행하고 그 결과를 비교한다.