• Journal of Digital Contents Society
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• v.5 no.4
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• pp.316-320
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• 2004

In this paper, we propose OFDM/QPSK technique for copyright protection of image data to insert watermark. And, we improve performance of restoration watermark by Reed-Solomon coding that robust burst error. In here, we consider several factors about external effect of image over OFDM/QPSK transmission system.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.191-197
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• 2013

In this paper, we implemented a paper currency recognition system using IR(infrared) sensor. The system has 32 channel IR sensor to measure the reflection and penetration quantity of light. The IR image of paper currency of 10-bit gray scale is used to differentiate the real and counterfeit paper currency with image information from 0 to 4095. The characteristics of IR image are recognized by brightness and darkness and the positions of bright and dark portions are different between real and counterfeit paper currency. The price of IR sensors were relatively high, however, it is good price in these days due to mass production to apply to counterfeit detection area. We used a software table having the IR characteristics of real paper currency to compare with the IR images of the input paper currency. The performance of the implemented system shows 1-2% error rates for Euro real paper currency and 0% error rates for various counterfeit paper currencies of several countries.

• 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 Digital Convergence
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• v.14 no.5
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• pp.263-271
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• 2016

Localizing an object in image is a common task in the field of computer vision. As the existing methods provide a detection for the single object in an image, they have an utilization limit for the use of the application, due to similar objects are in the actual picture. This paper proposes an efficient method of object localization for image recognition. The new proposed method uses color correlation back-projection in the YCbCr chromaticity color space to deal with the object localization problem. Using the proposed algorithm enables users to detect and locate primary location of object within the image, as well as candidate regions can be detected accurately without any information about object counts. To evaluate performance of the proposed algorithm, we estimate success rate of locating object with common used image database. Experimental results reveal that improvement of 21% success ratio was observed. This study builds on spatially localized color features and correlation-based localization, and the main contribution of this paper is that a different way of using correlogram is applied in object localization.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.1-7
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• 2008

Due to the development of ubiquitous computing, a wide variety of information is being produced and distributed rapidly in digital form. In this excess of information, it is not easy for users to search and find their desired information in short time. In this paper, we propose the personalized item recommendation using the image based filtering. This research uses the image based filtering which is extracting the feature from the image data that a user is interested in, in order to improve the superficial problem of content analysis. We evaluate the performance of the proposed method and it is compared with the performance of previous studies of the content based filtering and the collaborative filtering in the MovieLens dataset. And the results have shown that the proposed method significantly outperforms the previous methods.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.2
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• pp.168-174
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• 2008

Diagnosis on setteability based on human operator's experimental knowledge, which could be established by long term operation, is a limit factor to construction of automation control system in wastewater treatment plant. On-line SVI(Sludge Volume Index) analyzer was developed which can measure SV30 automatically by image capture and image analysis method. In this paper, information got by settling process was studied using On-line SVI analyzer for better operation & management of WWTPs. First, SV30 detection algorithm was developed using image capture and image analysis for settling test and it showed that automatic detection is feasible even if deflocculation and bulking was occurred. Second, turbidity assessment model was developed using image analysis.

• Korean Journal of Optics and Photonics
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• v.34 no.5
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• pp.192-201
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• 2023

The band-limited angular spectrum method (BL-ASM) causes aliasing errors due to spatial frequency control problems. In this paper, a sampling interval adjustment technique for phase holograms and a technique for reducing speckle noise and improving image quality using a deep-learningbased U-net model are proposed. With the proposed technique, speckle noise is reduced by first calculating the sampling factor and controlling the spatial frequency by adjusting the sampling interval so that aliasing errors can be removed in a wide range of propagation. The next step is to improve the quality of the reconstructed image by learning the phase hologram to which the deep learning model is applied. In the S/W simulation of various sample images, it was confirmed that the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were improved by 5% and 0.14% on average, compared with the existing BL-ASM.

• Journal of Conservation Science
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• v.38 no.2
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• pp.154-165
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• 2022

The color appearance of cultural heritage are essential factors for manufacturing technique interpretation, conservation treatment usage, and condition monitoring. Therefore, this study systematically established color reproduction procedures based on the digital color management system for the portrait of Gwon Eungsu. Moreover, various application strategies for recording and conserving the cultural heritage were proposed. Overall color reproduction processes were conducted in the following order: photography condition setting, standard color measurements, digital photography, color correction, and color space creation. Therefore, compared with the color appearance, the digital image applied to a camera maker profile indicated an average color difference of 𝜟10.1. However, the digital reproduction result based on the color management system exhibits an average color difference of 𝜟1.1, which is close to the color appearance. This means that although digital photography conditions are optimized, recording the color appearance is difficult when relying on the correction algorithm developed by the camera maker. Therefore, the digital color reproduction of cultural heritage is required through color correction and color space creation based on the raw digital image, which is a crucial process for documenting the color appearance. Additionally, the recording of color appearance through digital color reproduction is important for condition evaluation, conservation treatment, and restoration of cultural heritage. Furthermore, standard data of imaging analysis are available for discoloration monitoring.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.86-92
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• 2010

This paper proposes a new steganography scheme based on frequency domain using various image frames and collages that can protect the copyright of digital contents for users and securely perform to exchange the security information in the digital communication environments. The main idea of our proposed scheme is that the security informations related its copyright embed into the frequency domain of the image frame and collages when a user decorates the original image by using various image frames and collages. The strengths of our proposed scheme are as follows: (1) It allows to freely control the quantity of embedded information by changing the number of image frames and collages. (2) It is secure to variety image distortion attacks. (3) It maintains high PSNR(Peak Signal to Noise Ratio). As a result, the proposed steganography scheme can be used practically diverse multimedia security fields such as digital copyright protect, secure message communication and digital watermarking.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.42-50
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• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.