• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.205-210
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• 2008

A new approach is proposed for restoration of corrupted regions and segmentation in natural text images. The challenge is to fill in the corrupted regions on the basis of color feature analysis by second order symmetric stick tensor. It is show how feature analysis can benefit from analyzing features using tensor voting with chromatic and achromatic components. The proposed method is applied to text images corrupted by manifold types of various noises. Firstly, we decompose an image into chromatic and achromatic components to analyze images. Secondly, selected feature vectors are analyzed by second-order symmetric stick tensor. And tensors are redefined by voting information with neighbor voters, while restore the corrupted regions. Lastly, mode estimation and segmentation are performed by adaptive mean shift and separated clustering method respectively. This approach is automatically done, thereby allowing to easily fill-in corrupted regions containing completely different structures and surrounding backgrounds. Applications of proposed method include the restoration of damaged text images; removal of superimposed noises or streaks. We so can see that proposed approach is efficient and robust in terms of restoring and segmenting text images corrupted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.396-399
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• 2009

Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color, brightness and distance information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.637-644
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• 2021

In general, in the fields of computer vision, robotics, and augmented reality, the importance of 3D space and 3D object detection and recognition technology has emerged. In particular, since it is possible to acquire RGB images and depth images in real time through an image sensor using Microsoft Kinect method, many changes have been made to object detection, tracking and recognition studies. In this paper, we propose a method to improve the quality of 3D reconstructed images by processing images acquired through a depth-based (RGB-Depth) camera on a multi-view camera system. In this paper, a method of removing noise outside an object by applying a mask acquired from a color image and a method of applying a combined filtering operation to obtain the difference in depth information between pixels inside the object is proposed. Through each experiment result, it was confirmed that the proposed method can effectively remove noise and improve the quality of 3D reconstructed image.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.8
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• pp.491-498
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• 2016

This paper proposes a visualization method that expresses users' MBTI personality types based on the categorization method called 'Big Five Personality Traits' and their representative celebrities' facial images. This system has significance for visualizing traits from texts to images effectively. The entire system is composed of making backgrounds to represent traits of each MBTI category using 'Big Five Personality Traits' and showing facial images of celebrities with corresponding MBTI personality types. First, 'Big Five Personality Traits' classifies 16 MBTI types into four categories and each of category traits lays the foundation to make background using visual elements such as colors and lines. Second, celebrities' facial images are substituted for the corresponding literal explanation of each MBTI type. By adjusting the color saturation, users can distinguish relationship between the types intuitively. As a result, this system enables users to take information for their own / opposite / similar MBTI types simultaneously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Smart Media Journal
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• v.13 no.4
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• pp.57-64
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• 2024

Attributes such as material, color, and fit in fashion images are important factors for consumers to purchase clothing. However, the process of classifying clothing attributes requires a large amount of manpower and is inconsistent because it relies on the subjective judgment of human operators. To alleviate this problem, there is a need for research that utilizes artificial intelligence to classify clothing attributes in fashion images. Previous studies have mainly focused on classifying clothing attributes for either tops or bottoms, so there is a limitation that the attributes of both tops and bottoms cannot be identified simultaneously in the case of full-body fashion images. In this study, we propose a deep learning model that can distinguish between tops and bottoms in fashion images and classify the category of each item and the attributes of the clothing material. The deep learning models ResNet and EfficientNet were used in this study, and the dataset used for training was 1,002,718 fashion images and 125 labels including clothing categories and material properties. Based on the weighted F1-Score, ResNet is 0.800 and EfficientNet is 0.781, with ResNet showing better performance.

• Proceedings of the Korea Society of Costume Conference
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• 2005.10a
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• pp.114-115
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• 2005

• Journal of the Korean Graphic Arts Communication Society
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• v.15 no.2
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• pp.15-24
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• 1997

In DTP systems, satisfactory matching the appearance of displayed image on CRT and that of a reproduced binary image is very important. Most halftoning techniques assume that the printed color dots are square. However, most printers produce roughly circular dots. Thus, there is overlap between adjacent dots, and dots accupy adjcent space that should be empty space. These results are because the significant image distortion on the reproduced images. In this paper, we proposed a new tone correction digital halftoning method based on equi-visual perception characteristic.

• 대한방사선방어학회:학술대회논문집
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• 2011.04a
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• pp.66-67
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• 2011

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.175-178
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• 2003

This paper proposes a stereo image insertion technique on DCT coefficients using the embedded method developed in the digital watermarking in due consideration of compatibility with conventional 2D system such JPEG, and MPEG. In conventional transmission method users with conventional digital TV cannot watch the transmitted 3D image sequence as 2D image, because of affectivity of conventional 3D image compression. To give an answer, in this paper, DCT coefficients are changed according to its disparity on YCbCr channels. Our method can insert stereo images into a conventional image compression method based on DCT.