• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.317-318
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• 2006

There are lot of noises and errors in depth map image which is gotten by using a stereo camera. These errors are caused by mismatching of the corresponding points which occur in texture-less region of input images of stereo camera or occlusions. In this paper, we use a method which is able to get rid of the noises through post processing and reduce the errors of disparity values which are caused by the mismatching in the texture-less region of input images through the correlation between the depth map images and the input images. Then we propose a novel method which segments the object by using the improved disparity map images and projections.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.406-407
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• 2012

Texture transfer is a NPR technique for expressing various styles according to source (reference) image. By late 2000s, there are many texture transfer researches. But video base researchers are not active. Moreover, they didn't use important feature like directional information which need to express detail characteristics of target. So, we propose a new method to generate texture transfer animation (using video) with directional effect for maintaining temporal coherence and controlling coherence direction of texture. For maintaining temporal coherence, we use optical flow and confidence map to adapt for occlusion/disocclusion boundaries. And we control direction of texture for taking structure of input. For expressing various texture effects according to different regions, we calculate gradient based on directional weight. With these techniques, our algorithm can make animation result that maintain temporal coherence and express directional texture effect. It is reflect the characteristics of source and target image well. And our result can express various texture directions automatically.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.167-170
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• 2003

We propose stereoscopic video coding method using the syntax of MAC(Multiple auxiliary component) that was added to the MPEC-4 visual version 2 in order to describe the transparency of the video object. We also define the novel MAC's semantics in MPEG-4 that should support the proposed coding method. The major difference between the existing coding method and the proposed coding method is the addition of the residual texture coding. The proposed coding method assigns disparity map and residual texture to 3 components of MAC: one component for disparity map and the rest 2 components fer the luminance and chrominance data of the residual texture, respectively. The performance of the proposed method is evaluated in terms of PSNR by computer simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.195-206
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• 2016

The remote sensing technique using SAR data have many advantages when applied to the disaster site due to its wide coverage and all-weather acquisition availability. Although a single-pol (polarimetric) SAR image cannot represent the land surface better than a quad-pol SAR image can, single-pol SAR data are worth using for disaster-induced change detection. In this paper, an automatic change detection method based on a mixture of GGDs (generalized Gaussian distribution) is proposed, and usability of the textural features and intensity is evaluated by using the proposed method. Three ALOS/PALSAR images were used in the experiments, and the study site was Norita City, which was affected by the 2011 Tohoku earthquake. The experiment results showed that the proposed automatic change detection method is practical for disaster sites where the large areas change. The intensity information is useful for detecting disaster-induced changes with a 68.3% g-mean, but the texture information is not. The autocorrelation and correlation show the interesting implication that they tend not to extract agricultural areas in the change detection map. Therefore, the final tsunami-induced change map is produced by the combination of three maps: one is derived from the intensity information and used as an initial map, and the others are derived from the textural information and used as auxiliary data.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.1-10
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• 2022

China is a big country in animal fur industry. The total production and consumption of fur are increasing year by year. However, the recognition of fur in the fur production process still mainly relies on the visual identification of skilled workers, and the stability and consistency of products cannot be guaranteed. In response to this problem, this paper proposes a feature fusion-based animal fur recognition network on the basis of typical convolutional neural network structure, relying on rapidly developing deep learning techniques. This network superimposes texture feature - the most prominent feature of fur image - into the channel dimension of input image. The output feature map of the first layer convolution is inverted to obtain the inverted feature map and concat it into the original output feature map, then Leaky ReLU is used for activation, which makes full use of the texture information of fur image and the inverted feature information. Experimental results show that the algorithm improves the recognition accuracy by 9.08% on Fur_Recognition dataset and 6.41% on CIFAR-10 dataset. The algorithm in this paper can change the current situation that fur recognition relies on manual visual method to classify, and can lay foundation for improving the efficiency of fur production technology.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.736-746
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• 2016

In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.535-544
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• 2018

Developing a new texture path tool is crucial in 3D industries to automatically manage and set up texture paths for characters and environment modelings. For a better study, I compare the problems, methods and functions of the new tool(SongRepath tool) with other commonly used tools such as File Path Editor, Genie, He Texture Path. Next, I analyze the top down method system for these commonly used tools, and create a new bottom-up algorithm for a better use and efficiency. Finally, analyzing and comparing SongRepath tool with other tools in terms of operation in convenience, steps for results, checking number of Texture files, checking the numbers of new paths, checking the numbers of files not found, checking the numbers of path not changed, errors or problems, and availability of cancelation while proceeding the result. As a result, this study shows that SongRepath tool has less errors and saves more time on the processing works.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.375-381
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• 2009

In this paper, synthetic aperture radar (SAR) clutter images are simulated based on the extensive analyses for radar backscatter characteristics of various earth surfaces, and the simulated images are compared with measured SAR images. At first, the surface parameters including soil moisture content and surface roughness parameters and other parameters for vegetation canopies are measured for various surfaces. The backscattering coefficients for the surfaces are computed using theoretical and empirical models for surface scattering and the radiative transfer for vegetation-canopy scattering. Then, the digital elevation map (DEM) and land cover map (LCM) are used for the SAR image generation. The SAR impulse response (correlation function) is also employed to simulated reliable SAR images. Finally, the appropriate speckle and texture parameters for various earth surfaces are used for generating the SAR clutter images.

• Journal of Yeungnam Medical Science
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• v.39 no.1
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• pp.24-30
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• 2022

Background: Texture analysis has been used as a method for quantifying image properties based on textural features. The aim of the present study was to evaluate the usefulness of magnetic resonance imaging (MRI) texture analysis for the evaluation of viable ovarian tissue on the perfusion map of ovarian endometriosis. Methods: To generate a normalized perfusion map, subtracted T1-weighted imaging (T1WI), T1WI and contrast-enhanced T1W1 with sequences were performed using the same parameters in 25 patients with surgically confirmed ovarian endometriosis. Integrated density is defined as the sum of the values of the pixels in the image or selection. We investigated the parameters for texture analysis in ovarian endometriosis, including angular second moment (ASM), contrast, correlation, inverse difference moment (IDM), and entropy, which is equivalent to the product of area and mean gray value. Results: The perfusion ratio and integrated density of normal ovary were 0.52±0.05 and 238.72±136.21, respectively. Compared with the normal ovary, the affected ovary showed significant differences in total size (p<0.001), fractional area ratio (p<0.001), and perfusion ratio (p=0.010) but no significant differences in perfused tissue area (p=0.158) and integrated density (p=0.112). In comparison of parameters for texture analysis between the ovary with endometriosis and the contralateral normal ovary, ASM (p=0.004), contrast (p=0.002), IDM (p<0.001), and entropy (p=0.028) showed significant differences. A linear regression analysis revealed that fractional area had significant correlations with ASM (r²=0.211), IDM (r²=0.332), and entropy (r²=0.289). Conclusion: MRI texture analysis could be useful for the evaluation of viable ovarian tissues in patients with ovarian endometriosis.