• Journal of the Korean earth science society
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• v.26 no.7
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• pp.683-690
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• 2005

As remote sensing imagery with high spatial resolution (e.g. pixel resolution of 1m or less) is used widely in the specific application domains, the requirements of advanced methods for this imagery are increasing. Among many applicable methods, the texture image analysis, which was characterized by the spatial distribution of the gray levels in a neighborhood, can be regarded as one useful method. In the texture image, we compared and analyzed different results according to various directions, kernel sizes, and parameter types for the GLCM algorithm. Then, we studied spatial feature characteristics within each result image. In addition, a template matching program which can search spatial patterns using template images selected from original and texture images was also embodied and applied. Probabilities were examined on the basis of the results. These results would anticipate effective applications for detecting and analyzing specific shaped geological or other complex features using high spatial resolution imagery.

• Journal of KIISE:Software and Applications
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• v.32 no.1
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• pp.22-33
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• 2005

In this paper. we propose an image registration algorithm based on variable-sized blocks of ellipsoidal prototype model which is similar in shape to human face. While matching blocks, the existing cylindrical prototype model which only takes into account left and right curvature can accomplish a correct alignment on left and right images. But, registration errors are produced from up and down images because the cylindrical prototype model not reflects characteristics of head shape and jaw structure of human. The proposed method is a block matching algorithm which uses variable-sized blocks with considering left-right and up-down curvature of ellipsoidal face model and can correctly align images by using the correlation between them. We then adapt image mosaic technique to generate a face texture from aligned images. For this purpose, we stitch them with assigning linear weights according to the overlapped region and remove ghost effects to make more realistic facial texture.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.979-989
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• 2016

Traversable region detection is an essential step for advanced driver assistance systems and self-driving car systems, and it has been conducted by detecting lanes from input images. The performance can be unreliable, however, when the light condition is poor or there exist no lanes on the roads. To solve this problem, this paper proposes an algorithm which utilizes the information about the number of lanes and texture analysis. The proposed algorithm first specifies road region candidates by utilizing the number of lanes information. Among road region candidates, the road region is determined as the region in which texture is homogeneous and texture discontinuities occur around its boundaries. Traversable region is finally detected by dividing the estimated road region with the number of lanes information. This paper combines the proposed algorithm with a lane detection-based method to construct a system, and simulation results show that the system detects traversable region even on the road with poor light conditions or no lanes.

• Journal of the Korea Computer Graphics Society
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• v.15 no.1
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• pp.17-23
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• 2009

We present a simple new idea to improve the quality of exemplar based texture synthesis using multiple rotated input exemplars. Our algorithm successfully obtain rotational synthesis feature variations and manages to reduce the artifacts in the results, especially patch seams due to the structure of the exemplars provided which have been inappropriate for previous neighborhood matching synthesis algorithms. Our algorithm is parallel in nature, thus it is possible to implement our algorithm using GPU or multi-core CPU to accelerate synthesis process.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.137-140
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• 2001

This paper has been studied for alphabet recognition by using MPEG-7 descriptors. As an application of MPEG-7, the algorithms in this paper have employed Homogeneous Texture descriptor and Edge Histogram descriptor. For confident matching a voting system is used with a tree structure,

• Journal of Korea Multimedia Society
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• v.18 no.8
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• pp.901-908
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• 2015

Methods of detecting, describing, matching image features, like corners and blobs, have been actively studied as a fundamental step for image processing and computer vision applications. As one of feature description/matching methods, LLAH(Locally Likely Arrangement Hashing) describes image features based on the geometric relationship between their neighbors, and thus is suitable for scenes with poor texture. This paper presents a modified LLAH algorithm, which includes the image features themselves for robustly describing the geometric relationship unlike the original LLAH, and employes a voting-based feature matching scheme that makes feature description much simpler. Then, this paper quantitatively analyzes its performance with synthetic images in the presence of Gaussian noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3806-3825
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• 2016

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L₂ distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.764-776
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• 2008

Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.896-906
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• 2014

In this paper, a real-time dual-mode temporal synchronization and compensation method based on a new reliability measure in stereoscopic video is proposed. The goal of temporal alignment is to detect the temporal asynchrony and recover synchronization of the two video streams. The accuracy of the temporal synchronization algorithm depends on the 3DTV contents. In order to compensate the temporal synchronization error, it is necessary to judge whether the result of the temporal synchronization is reliable or not. Based on our recently developed temporal synchronization method[1], we define a new reliability measure for the result of the temporal synchronization method. Furthermore, we developed a dual-mode temporal synchronization method, which uses a usual texture matching method and the temporal spatiogram method[1]. The new reliability measure is based on two distinctive features, a dynamic feature for scene change and a matching distinction feature. Various experimental results show the effectiveness of the proposed method. The proposed algorithms are evaluated and verified through an experimental system implemented for 3DTV.

• The Journal of Korean Association of Computer Education
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• v.7 no.5
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• pp.111-120
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• 2004

The MPEG-7 standard defines a set of descriptors that extracts low-level features such as color, texture and object shape from an image and generates metadata in order to represent these extracted information. But the matching performance for image mining ma y not be satisfactory by u sing only on e of these features. Rather than by combining these features we can achieve a better query performance. In this paper we propose a new image retrieval technique for image mining that combines the features extracted from MPEG-7 visual color and texture descriptors. Specifically, we use only some specifications of Scalable Color Descriptor (SCD) and Non-Homogeneous Texture Descriptor also known as Edge Histogram Descriptor (EHD) for the implementation of the color and edge histograms respectively. MPEG-7 standard defines $l_{1}$-norm based matching in EHD and SCD. But in our approach, for distance measurement, we achieve a better result by using cosine similarity coefficient for color histograms and Euclidean distance for edge histograms. Our approach toward this system is more experimental based than hypothetical.