• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.50-55
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• 2006

This paper presents a scheme which scrambles and descrambles images from multiple video channels. A combined image frame is formed by concatenating the incoming frames from channels in a two dimensional array. This algorithm employs an encryption scheme on row and column numbers of the combined image frame and thereby yields an encrypted combined image. The proposed algorithm is to encrypt multiple images at a time since it recomposes images from multiple video channels yielding one by composite image, and encrypts the composite image resulting In higher security.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1484-1489
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• 2004

Given a video frame in terms of its 8${\times}$8 block-DCT coefncients, we wish to obtain a downsized or upsized version of this Dame also in terms of 8${\times}$8 block DCT coefficients. The DCT being a linear unitary transform is distributive over matrix multiplication. This fact has been used for downsampling video frames in the DCT domains in Dugad's, Mukherjee's, and Park's methods. The downsampling and upsampling schemes combined together preserve all the low-frequency DCT coefficients of the original image. This implies tremendous savings for coding the difference between the original frame (unsampled image) and its prediction (the upsampled image).This is desirable for many applications based on scalable encoding of video. In this paper, we extend the earlier works to various DCT sizes, when we downsample and then upsample of an image by a factor of two. Through experiment, we could improve the PSM values whenever we increase the DCT block size. However, because the complexity will be also increase, we can say there is a tradeoff. The experiment result would provide important data for developing fast algorithms of compressed-domain image/video resizing.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.115-122
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• 2019

CCTV(Closed-Circuit Television) is increasingly exposed to CCTV per person as the number of installations increases every year for accident prevention and facility safety. The intelligent video surveillance system technology is attracting attention to the privacy protection of exposed subjects. The intelligent video surveillance system performs a process for the privacy protection so as to perform the action type of the subject and the judgment of the situation in the simple identification of the photographed image data, or to prevent the information, from which the information of the photographed subject is exposed. The proposed technique is applied to the video surveillance system and converts the original image information taken from the video surveillance system into similar image information so that the original image information is not leaked to the outside. In this paper, we propose an image conversion mechanism that inserts a virtual face image that approximates a preset similarity.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.4-7
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• 2010

3D 콘텐츠에 대한 관심이 증가함에 따라 3D 시청 및 제작에 대한 가이드라인의 필요성도 함께 증가하고 있다. 3D 안정 시청 가이드 라인은 3D 시청으로 인한 시청자의 시각적 불쾌감이나 피로감을 방지하는데 목적을 두고 있으며, 최근 일본의 3DC에서는 과도한 수렴-조절 불일치를 방지하기 위해 양안 시차 $1^{\circ}$를 쾌적 시차 범위로 권고하고 있다. 하지만 이 쾌적 시차는 절대적인 수치가 아니며, 콘텐츠의 특성 및 시청 조건에 따라 변하는 것으로 추정된다. 본 논문에서는 쾌적 시차를 갖는 3D 영상 콘텐츠에서 객체의 모션으로 인해 양안시차가 시공간적으로 변할 때, 야기되는 시각적 불편함의 변화에 대하여 관찰한다. 특히, 깊이 방향 모션 및 수평 방향 모션에서 객체의 속도 변화에 대한 시각적 피로감의 정도를 주관적 평가를 통하여 측정한다.

• ETRI Journal
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• v.29 no.3
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• pp.353-362
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• 2007

In this paper, we propose a novel unsupervised video object extraction algorithm for individual images or image sequences with low depth of field (DOF). Low DOF is a popular photographic technique which enables the representation of the photographer's intention by giving a clear focus only on an object of interest (OOI). We first describe a fast and efficient scheme for extracting OOIs from individual low-DOF images and then extend it to deal with image sequences with low DOF in the next part. The basic algorithm unfolds into three modules. In the first module, a higher-order statistics map, which represents the spatial distribution of the high-frequency components, is obtained from an input low-DOF image. The second module locates the block-based OOI for further processing. Using the block-based OOI, the final OOI is obtained with pixel-level accuracy. We also present an algorithm to extend the extraction scheme to image sequences with low DOF. The proposed system does not require any user assistance to determine the initial OOI. This is possible due to the use of low-DOF images. The experimental results indicate that the proposed algorithm can serve as an effective tool for applications, such as 2D to 3D and photo-realistic video scene generation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.42-47
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• 2007

Video Segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries. But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes that adaptive trimmed mean filter for resolving the over segmentation of image. Simulation result, we confirm that proposed ATM filter improves the performance to remove noise and reduces damage for the clear degree of image in case of the noise ratio of 20% and over.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.631-644
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• 2002

In this paper efficient algorithms for content-based video retrieval using motion information are proposed, including temporal scale-invariant retrieval and temporal scale-absolute retrieval. In temporal scale-invariant video retrieval, the distance transformation is performed on each trail image in database. Then, from a given que교 trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image, since the intensity of each pixel in distance image represents the distance from that pixel to the nearest edge pixel. For temporal scale-absolute retrieval, a new coding scheme referred to as Motion Retrieval Code is proposed. This code is designed to represent object motions in the human visual sense so that the retrieval performance can be improved. The proposed coding scheme can also achieve a fast matching, since the similarity between two motion vectors can be computed by simple bit operations. The efficiencies of the proposed methods are shown by experimental results.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.167-175
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• 2002

Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.1
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• pp.200-216
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• 2021

This article considers short-form fashion videos as distinguished from fashion films, defines the concept, details the expressive characteristics of short-form fashion video, and reveals the method of producing it. For the methodology, a literature review was conducted to derive the concept and expression techniques. A case study was also performed to define the expressive characteristics. Five short-form fashion videos were also produced based on the results. The final results are as follows. First, short-form fashion video was defined as a fashion medium on the purpose of fashion communication within 60 seconds and classified by three digital image formats. Second, the result of analyzing the expression of the short-form fashion video shows the simplicity and reconstitution, characterization and remediation, borderless and expansion, and synesthesia trigger of the fashion image. Third, five short-form fashion videos were produced based on the theme of the digital garden. It shows that the short-form fashion video intensively expresses the content as a medium whose sensational expression is more prominent than the composition of the story by the short running time that reflects the taste of digital mainstream.