• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.91-99
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• 2006

Pre-processing is one of image processing techniques to enhance image quality or appropriately convert a given image into another form for a specific purpose. An 8 bit depth map obtained by a depth camera usually contains a lot of noisy components caused by the characteristics of depth camera and edges are also more distorted by the quality of a source object and illumination condition comparing with edges in RGB texture image. To reduce this distortion, we use noise removing filters, but they are only able to reduce noise components, so that distorted edges of depth map can not be properly recovered. In this paper, we propose an algorithm that can reduce noise components and also enhance the quality of edges of depth map by using edges in RGB texture. Consequently, we can reduce errors in multi-view stereo image synthesis process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.885-892
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• 2013

In this paper, we propose a method of effectively segmenting character regions by using texture and depth features in 3D stereoscopic images. The suggested method is mainly composed of four steps. The candidate character region extraction step extracts candidate character regions by using texture features. The character region localization step obtains only the string regions in the candidate character regions. The character/background separation step separates characters from background in the localized character areas. The verification step verifies if the candidate regions are real characters or not. In experimental results, we show that the proposed method can extract character regions from input images more accurately compared to other existing methods.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.773-776
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• 1998

In this paper, we propose an efficient multi-view images coding algorithm which finds the optimal texture from the restricted number of multi-view images. The X-Y plane of the normalized object space is divided into triangular patches. The depth value of the node is determined by applying the block based disparity compensation method and then the texture of the each patch is extracted by applying the affine transformation patch is extracted by applying the affine transformation based disparity compensation method to the multi-view images. We restricted the number of images contributed to determining the texture comapred to traditional methods which use all the multi-view images in the texture extraction. Experimental results show that the SNR of images encoded by the proposed algorithm is better than that of imaes encoded by the traditional method by the amount about 0.2dB for the test sets of multi-view images called dragon, kid, city and santa. The recovered images from the encoded data by the proposed method show the better visual images than the recovered images from the encoded data by the traditional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.37-42
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• 2018

With advancements in digital image production technology, the branch of stereoscopic image technology has also been undergoing active development. Accordingly, research and development on cutting-edge display products for mounting stereoscopic images are currently being pursued. There are various problems that can occur when viewing 3D images. Because viewers feel visual fatigue while perceiving the depth of the images provided via an artificial method, a negative human factor such as visual fatigue has become one of the most prominent concerns, especially as it is a factor that affects the ongoing maintenance of 3D images. Therefore, by identifying the factors affecting the depth of the graphic images provided in 2D images, and subsequently using this information to develop an image processing method, we conducted depth-related experiments and analysed them under the assumption that stereoscopic images could be reproduced without visual fatigue. Thus, we analysed the most significant factors related to depth and verified the interactions by performing depth-related factors-based ANOVA variance analysis by differentially applying the texture, colour temperature, and contrast ratio to graphic images. We determined the significance of the factors related to depth and proposed a method to improve depth based on an analysis of the results of the experiments conducted in this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.11-22
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• 2002

The design of optimal filter yielding optimal texture feature separation is a most effective technique in many torture analyzing areas, such as perception of surface, object, shape and depth. But, most optimal filter design approaches are restricted to the issue of computational complexity and supervised problems. In this paper, Our proposed method yields new insight into the design of optimal Gabor filters for segmenting multiple texture images. The optimal frequency of Gator filter is turned to the optimal frequency of the distinct texture in frequency domain. In order to show the performance of the designed filters, we have attempted to build a various texture images. Our experimental results show that the performance of the system is very successful.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.197-200
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• 2011

In this paper, we propose a multi-view stereoscopic image synthesis algorithm for 3DTV system using depth information with an RGB texture from a depth camera. The proposed algorithm synthesizes multi-view images which a virtual convergence camera model could generate. Experimental results showed that the performance of the proposed algorithm is better than those of conventional methods.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.287-301
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• 2006

Two experiments were performed to investigate effects of background depth information on the judgment of two-dimensional shapes, using the Posner et al.'s(1969) physical match task. In both experiments, the focus was on whether the background depth information affects the decisions of physical shape sameness of two letters or figures presented successively. In Experiment 1, artificially constructed rues of linear perspective and texture gradient were used, whereas cues contained in a real road situation were used in Experiment 2. The results of both experiments showed that the depth cues affect the perception of two-dimensional shapes. That is, when two stimuli of the same physical shape were likely to be perceived differently due to the given depth cues, response accuracies('yet' in this case) decreased and reaction tines of physical match increased. And when two stimuli of the different physical shape were likely to be perceived the same due to the given depth cues, response accuracies('no' in this case) decreased and reaction times of physical match increased likewise. These results wert discussed in terms of some conceptual methodological problems of the previous studies on the shape constancy and the directions of future research.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.584-586
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• 2007

3D virtual modeling such as creation of a cyber city or landscape, or making a 3D GIS requires realistic textures. Automatic texture extraction using close range images is not yet efficient or easy in terms of data acquisition and processing. In this paper, common problems associated with automatic texture extraction from aerial photographs are explored. The ZI-buffer, which has depth and facet ID fields, is proposed to remove hidden pixels. The ZI-buffer algorithm reduces memory burden and identifies visible facets. The correct spatial resolution for facet gridding is tested. Error pixels in the visibility map were removed by filtering.

• The Korean Journal of Ecology
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• v.20 no.2
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• pp.133-143
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• 1997

From 1984 to 1989 reclaimed coastal lands in Choongnam Province of the western coast of Korea were studied for soil texture at three sites(Daeho, Hyundai A and Hyundai B) and for desalination one site(Hyundai B). The soil textures of varied sites in Hyundai A were horizontally similar and composed of 39-40% clay, 40-49% silt and 8-14% sand. But those in Da돼 and Hyundai B differed horizontally in the same area and vertically at the same site. Soil texures of Da돼 were composed of 15-17% clay, 30-45% silt and 40-55% sand and those of Hyundai B were composed of 22-45% clay, 26-49% silt and 17-31% sand. The measured electrical conductivity(EC), which represents whole salt content of the reclaimed soil, decreased year by year. The vertical distribution of the EC changed temporally and spatially in the upper zone above a 50 cm depth but not in The lower zone below a 50 cm depth. The EC valus of the soil were inversely proportional to the magnitued of annual precipitation, evaporation and the numbers of rainy days with r equalling -0.97. But the annual decrease of the EC was directly proportional to climatic factors with r=0.7. Salt in the reclaimed land was leached out by the percolative action of surplus rain water, or moved up by evaporation and carried away by running rain water. The running out of the salt on the soil surface was most efficiently carried out over 10 mm precipitation per day.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.