• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1855-1862
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• 2010

In virtual reality, there are increasing qualitative development in service technologies for realtime interaction system development, 3- dimensional contents, 3D TV and augment reality services. These services experience difficulties to generate depth value that is essential to recover 3D space to form solidity on existing contents. Hence, research for the generation of effective depth-map using 2D is necessary. This thesis will describe a shortcoming of an existing depth-map generation for the recovery of 3D space using 2D image and will propose an enhanced depth-map generation algorithm that complements a shortcoming of existing algorithms and utilizes the definition of depth direction based on the vanishing point within image.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1183-1195
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• 2020

Visual saliency detection is an essential task because it is an important part of various vision-based applications. There are many techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is limited. In this paper, we introduce a simple approach for saliency detection in infrared images based on the thresholding technique. The input image is thresholded into several Boolean maps, and an initial saliency map is calculated as a weighted sum of the created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and a Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method has high performance when applied to real-life data.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.697-698
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• 2006

In this paper, we propose a new scheme to generate multi-view images using a depth-image-based rendering (DIBR) technique. In order to improve the quality of multi-view images at newly exposed areas during mesh-based rendering, we preprocess the depth map using a Gaussian smoothing filter. Previous algorithms apply a smoothing filter to the whole depth map even if the depth map is collapsed. After extracting objects from the depth map, we apply the smoothing filter to their boundaries. Finally, we cannot only maintain the depth quality, but also generate high quality multi-view images. Experimental results show that our proposed algorithm outperforms previous works and supports an efficient depth keying technique.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.547-557
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• 2019

To extract the depth map from a single image, a number of CNN-based deep learning methods have been performed in recent research. In this study, the GAN structure of Pix2Pix is maintained. this model allows to converge well, because it has the structure of the generator and the discriminator. But the convolution in this model takes a long time to compute. So we change the convolution form in the generator to a depthwise convolution to improve the speed while preserving the result. Thus, the seven down-sizing convolutional hidden layers in the generator U-Net are changed to depthwise convolution. This type of convolution decreases the number of parameters, and also speeds up computation time. The proposed model shows similar depth map prediction results as in the case of the existing structure, and the computation time in case of a inference is decreased by 64%.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.555-564
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• 2014

The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.

• Journal of KIISE
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• v.42 no.12
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• pp.1474-1479
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• 2015

With mobile devices showing marked improvement in performance in the age of the Internet of Things (IoT), there is demand for rapid processing of the extensive amount of multimedia big data. However, because research on image searching is focused mainly on increasing accuracy despite environmental changes, the development of fast processing of high-resolution multimedia data queries is slow and inefficient. Hence, we suggest a new distributed image search algorithm that ensures both high accuracy and rapid response by using feature extraction of distributed images based on MapReduce, and solves the problem of memory scalability based on BIRCH indexing. In addition, we conducted an experiment on the accuracy, processing time, and scalability of this algorithm to confirm its excellent performance.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.81-91
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• 1994

A DCT map and new cldebook design algorithm based on a two-dimension discrete cosine transform (2D-DCT) is presented for coder of image vector quantizer. We divide the image into smaller subblocks, then, using 2D DCT, separate it into blocks which are hard to code but it bears most of the visual information and easy to code but little visual information, and DCT map is made. According to this map, the significant features of training image are extracted by using the 2D DCT. A codebook is generated by partitioning the training set into a binary tree based on tree-structure. Each training vector at a nonterminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. Compared with the pairwise neighbor (PPN) and classified VQ(CVQ) algorithm, about 'Lenna' and 'Boat' image, the new algorithm results in a reduction in computation time and shows better picture quality with 0.45 dB and 0.33dB differences as to PNN, 0.05dB and 0.1dB differences as to CVQ respectively.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.368-378
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• 2015

3D conversion technology has been studied over past decades and integrated to commercial 3D displays and 3DTVs. The 3D conversion plays an important role in the augmented functionality of three-dimensional television (3DTV), because it can easily provide 3D contents. Generally, depth cues extracted from a static image is used for generating a depth map followed by DIBR (Depth Image Based Rendering) rendering for producing a stereoscopic image. However except some particular images, the existence of depth cues is rare so that the consistent quality of a depth map cannot be accordingly guaranteed. Therefore, it is imperative to make a 3D conversion method that produces satisfactory and consistent 3D for diverse video contents. From this viewpoint, this paper proposes a novel method with applicability to general types of image. For this, saliency as well as edge is utilized. To generate a depth map, geometric perspective, affinity model and binomic filter are used. In the experiments, the proposed method was performed on 24 video clips with a variety of contents. From a subjective test for 3D perception and visual fatigue, satisfactory and comfortable viewing of 3D contents was validated.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.286-296
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• 2005

This paper presents a stereo-based image compression and transmission system for 3D realistic television. In the proposed system, a disparity map is extracted from an input stereo image pair and the extracted disparity map and one of two input images are transmitted or stored at a local or remote site. However, correspondences can not be determined in occlusion areas. Thus, it is not easy to recover 3D information in such regions. In this paper, a reconstruction image compensation algorithm based on error block concealment and in-loop filtering is proposed to minimize the reconstruction error in generating stereo image pair. The effectiveness of the proposed algorithm is shown in term of objective accuracy of reconstruction image with several real stereo image pairs.

• Journal of the Korean Society of Clothing and Textiles
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• v.14 no.2
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• pp.129-136
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• 1990

The purpose of the study was to develope brand positioning map for ladies' ready-to-wear, to find out evaluative criteria in perception and preference to brands, and to persent the relationship between consumer's characteristics and brand preference. Subjects were selected for the housewives of middle and high socioeconomic classes living in Seoul area. A questionnaire including items of life style, self image, similarity between brands, preference degree to brands, and demographic variables was developed for the empirical study. The questionnaire was administrated to 137 housewives during fall in 1989. Data were analyzed by cluster analysis and multidimensional scaling method. The study had two research problems. The first research problem was to construct a brand perceptual map for ladies' ready-to-wear brands, selected for the study The perceptual map was constructed on the basis of brand similarity scores by multidimensional scaling method. As a result, brands were grouped into 4 clusters, and evaluative criteria for perceptual map were found to be fashionability (classic- fashionable) and familiarity (familiar-unfamiliar). The second problem was to construct a brand preference map for ladies' ready-to-wear brands, selected for the study. The preference map was constructed on the basis of brand preference scores by multidimensional scaling method. As a result, the brands were grouped into 4 clusters and evaluative critiera for preference map were found to be fashionability (unfashionable-fashionable) and image to age (mature-young directed). Also was shown the relationship among self image, age, socioeconomic class, and brand preference. The multidimensional scaling method was found to be useful as well as valid instrument for brand positioning research and the result can be utilized for establishing strategies for ladies' ready-to-wear brands.