• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.663-673
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• 2011

Applications of two dimensional image codes like QR and color code on mobile phone are spreading widely and in lieu of that, better decoding technology and platform designs are required. Futhermore "Bokode" technology which recognizes the defocus-blur image information from imperceptible visual tiny code on ordinary digital camera has been announced newly. There is an urgent need for competitive strategies to activate 2D image code industry and R&D under smart environment. This paper focused on suggesting valuable idea and practical task through investigation and analysis required for supporting of thus strategy construction. Description consist of introduction, technological tendency for R&D, patent and market, implementation task, conclusion and suggestion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.3029-3034
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• 2014

The paper describes the scleral diagnostic system implementation for human eyes by using the scleral color code and vessels sign pattern code generations. The system is based on the high performance DSP image signal processor, programmable gain control for preprocessing and RISC SD frames storage. RGB image signals are optimized by PGC, the edge image is detected form the gray image converted. The processing algorithms are executed by scleral color code generation and scleral vessels sign pattern code creation for discriminating and matching. The scleral symptomatic color code is generated by YCbCr values at memory map tolerated and the vessel sign pattern code is created by digitizing the 24 clock and 13 ring zones, overlay matching and tolerances. The experimental results for performance are that the system runs 40ms, and the color and pattern for diagnostic errors are around 20% and 24% on average. The system and technique enable a scleral diagnosis with subdividing the patterns and patient database.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.281-288
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• 2009

This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

• IE interfaces
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• v.15 no.1
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• pp.20-25
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• 2002

In this research, a nameplate engraving system for images and texts downloaded through Internet on nameplate is developed. The system consists of two subsystems: thinning algorithm and NC code generation module. In the thinning algorithm, the concept of connectivity is used and center lines of images and texts, which will be used as NC tool paths, can be obtained successfully. Because the center lines are composed of a lot of pixels, NC code would be too long. In the NC code generation module, many useless pixel data are removed and linear interpolation algorithm is applied to only the remaining pixels. By performing actual experiments, the thinning algorithm and the NC code generation module are verified.

• Fashion & Textile Research Journal
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• v.6 no.5
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• pp.549-557
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• 2004

The purpose of this study is to investigate design properties affecting in evaluated image by adult women's town wear in un-limited circumstance. The stimulus, adult women's town wear, were collected from shopping mall, department stores and churches and evaluated by 20's 150 people. Through the estimations, the 76 pictures of 'good image' and 65 pictures of 'bad image', were selected and analyzed by classification categories. The results were as follows : 1) 'Good Image' is classified 6 groups which are like active casual, feminine casual, adult casual, modern, sporty casual, and elegance. 2) "Bad Image' is classified 5 groups which are like easy casual, active casual, soft casual, modern casual, and feminine casual. 3) Central code of adult women's town wear from 'Good Image' are simple, bright, and harmony and 'Bad Image' are complicate, heavy, and inharmony. The coordination, how to wear, is very important to evaluate image of women's town wear with other properties. Also, body shape appeared by important variable in evaluation.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.159-175
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• 2015

The two-dimensional QR code has advantages such as directional nature, enough data storage capacity, ability of error correction, and ability of data restoration. There are two major issues like speed and correctiveness of recognition in the two-dimensional QR code. Therefore, this paper proposes a morphology-based algorithm of detecting the interest region of a barcode. Our research contents can be summarized as follows. First, the interest region of a barcode image was detected by close operations in morphology. Second, after that, the boundary of the barcode are detected by intersecting four cross line outside in a code. Three, the projected image is then rectified into a two-dimensional barcode in a square shape by the reverse-perspective transform. In result, it shows that our detection and recognition rates for the barcode image is also 97.20% and 94.80%, respectively and that outperforms than previous methods in various illumination and distorted image environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2363-2369
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• 2016

In this paper, we propose three-dimensional (3D) quick-response (QR) code generation technique using passive 3D integral imaging and computational integral imaging reconstruction technique. In our proposed method, we divide 2D QR code into 4 planes with different reconstruction depths and then we generate 3D QR code using synthetic aperture integral imaging and computational reconstruction. In this 3D QR code generation process, we use integral imaging which is one of 3D imaging technologies. Finally, 3D QR code can be scanned by reconstructing and merging 3D QR codes at 4 different planes with computational reconstruction. Therefore, the security level for QR code scanning may be enhanced when QR code is scanned. To show that our proposed method can improve the security level for QR code scanning, in this paper, we carry out the optical experiments and computational reconstruction. In addition, we show that 3D QR code can be scanned when reconstruction depths are known.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.20-27
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• 2010

This paper proposes a saturation compensating method by embedding pseudo-random code information in wavelet packet based colorization algorithm. In the color-to-gray process, an input RGB image is converted into YCbCr images, and a 2-level wavelet packet transform is applied to the Y image. And then, color components of CbCr are embedded into two sub-bands including minimum amount of energy on the Y image. At this time, in order to compensate the color saturations of the recovered color image during the printing and scanning process, the maximum and minimum values of CbCr components of an original image are also embedded into the diagonal-diagonal sub-band by a form of pseudo-random code. This pseudo-random code has the maximum and minimum values of an original CbCr components, and is expressed by the number of white pixels. In the gray-to-color process, saturations of the recovered color image are compensated using the ratio of the original CbCr values to the extracted CbCr values. Through the experiments, we can confirm that the proposed method improves color saturations in the recovered color images by the comparison of color difference and PSNR values.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.113-116
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• 2021

As artificial intelligence technologies, including deep learning, develop, these technologies are being introduced to code similarity analysis. In the traditional analysis method of calculating the graph edit distance (GED) after converting the source code into a control flow graph (CFG), there are studies that calculate the GED through a trained graph neural network (GNN) with the converted CFG, Methods for analyzing code similarity through CNN by imaging CFG are also being studied. In this paper, to determine which approach will be effective and efficient in researching code similarity analysis methods using artificial intelligence in the future, code similarity is measured through funcGNN, which measures code similarity using GNN, and Siamese Network, which is an image similarity analysis model. The accuracy was compared and analyzed. As a result of the analysis, the error rate (0.0458) of the Siamese network was bigger than that of the funcGNN (0.0362).

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.400-412
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• 2020

The "genderless fashion" style adopted by 20 to 30-year-olds in Korea cannot be ignored in the consumer fashion code. This study investigated self-images of Korean genderless fashion consumers through in-depth interviews. Interview analyses confirmed that Korean genderless fashion consumers express their self-image through clothing. As the theoretical framework, this study used Lacan's concept of desire to classify the types of self-image consumers want to express. The results are classified into three subject types: those who pursue self-fulfillment, those who pursue fulfillment from others, and those who pursue endless fulfillment through a self-image. This reflects various factors and the subjects' desires. Further, a subject's desire to present a specific self-image was an important factor in understanding the genderless fashion style. The study results revealed that modern fashion is an "unconscious" field of self-expression that crucially reflects individual desires. The study also contributes to the understanding of the concept of self-image at large.