• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.181-184
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• 2000

In this paper, we propose new features for describing texture images by using multi-channel Gabor filter and log-polar transform based on human visual system (HVS). Gabor features are extracted by the mean and standard deviation of energy in Gabor response, followed by Fourier series extension. Log-polar features are extracted by log-polar transform and projection. The proposed texture descriptor performs reasonably well with less number of features than other texture descriptors, which has been verified by experiments using some texture images of MPEG-7 data set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.3
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• pp.88-96
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• 2000

The objective of this study is to evaluate the preference and visual characteristic of users according to the location of benches at urban community parks. The types of benches are separated into four patterns and located in four representative places at urban community parks. Each relations between visual preference and adjective related factors are calibrated by the estimated results of Pearson correlation coefficient. Moreover, the factors which affect the visual preference are obtained by multiple regression analysis and to calibrate the each factors significant level, the method of multivariate variance analysis is applied. The results of this study are summzrized as belows: 1. Four types of factors which consist the visual characteristic are classified as emotional factor of visual images(aesthetic factor(F1), texture related factor(F2)) and physical factor(physical factor(F3), transformable factor(F4)). Each factor's eigenvalue is appears as 5.27∼1.78 and the eigenvalue of emotional factor of visual images is more higher than the physical factor. 2. The correlation coefficient between visual preference according to the location of benches(X21) and aesthetic factor(f1) is estimated as 0.79, which is highest value among the four factors. And the correlation coefficient of texture related factor(f2), physical factor(F3) and transformable factor(F4) is estimated as 0.14, 0.04 and 0.08 respectively. 3. The visual preference of users according to the location of benches is greatly affected by the emotional factor of visual images(F1, F2) and the physical factor(F3, F4) are poorly related. The results of this study suggest the effective guidelines for the location of leisure facilities. Moreover the design and planning of leisure facilities at the urban community park have to be reexamined. What must be examined from now on is as follows: First, the preference research of rest facilities in the urban park through the multiple approach must be carried out continuously. Second, the research about the visual quality of the environmental sight observed in sitting on the bench as well as the visual quality of the showed object and place needs to be supported. Nevertheless, through this study the utilization into the useful data of the plan and the design for the systematic disposition of landscape architecture equipments centered on the users can be expected.

• 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.

• Korean Institute of Interior Design Journal
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• v.20 no.2
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• pp.147-155
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• 2011

The purpose of this study is to grope for plan methods through analyzing preferences on expression methods of materials for visual differentiation in hosing space. The results are as follows : First, we could know that finish material is the important element to make differential design in housing space. It is a effective method to use the color and material of finish materials. Second, we could find they preferred woods in materials and Y color, N9.5, bright and light in colors through grasping preference about types in material elements. The preferred texture is soft and the preferred patterns are solid and geometry. Third, it is a good method to mix materials which give us different season feeling, and to mix colors which are different tones to lead the differential design by materials in housing space. In case texture and patterns, what we mix similar things is the effective method. Fourth, preference of the expression method is manifested differently depending on the selected elements. so when we plan the housing, we have to consider that. lastly, I think this study will be a basic data on a study to differentiate the design of the residential space.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2059-2064
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• 2004

Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

• The Journal of Natural Sciences
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• v.5 no.2
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• pp.33-38
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• 1992

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented for multime-dia teleconference. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. We compare the coding efficiency of this technique with that of a well established technique (discrete cosine transform (DCT) image coding).

• ETRI Journal
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• v.20 no.3
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• pp.272-283
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• 1998

In this paper, we propose efficient content-based image retrieval methods using the automatic extraction of the low-level visual features as image content. Two new feature extraction methods are presented. The first one os an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1899-1902
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• 2003

Recently several methods have been developed for the virtual space construction. Generally, most of the methods are geometric-based rendering technic, but they are difficult to construct real-time rendering because of large data. In this paper, we present a three dimension image-based rendering method that enable a constant speed of real-time rendering regardless of object complexity in virtual space. The Proposed method shows good performance for the virtual space construction with high complexity.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.397-405
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• 2004

Texture mapping is the process of covering 3D models with texture images in order to increase the visual realism of the models. For proper mapping the coordinates of texture images need to coincide with those of the 3D models. When projective images from the camera are used as texture images, the texture image coordinates are defined by a camera calibration method. The texture image coordinates are determined by the relation between the coordinate systems of the camera image and the 3D object. With the projective camera images, the distortion effect caused by the camera lenses should be compensated in order to get accurate texture coordinates. The distortion effect problem has been dealt with iterative methods, where the camera calibration coefficients are computed first without considering the distortion effect and then modified properly. The methods not only cause to change the position of the camera perspective line in the image plane, but also require more control points. In this paper, a new iterative method is suggested for reducing the error by fixing the principal points in the image plane. The method considers the image distortion effect independently and fixes the values of correction coefficients, with which the distortion coefficients can be computed with fewer control points. It is shown that the camera distortion effects are compensated with fewer numbers of control points than the previous methods and the projective texture mapping results in more realistic image.