• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.83-86
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• 1986

In this paper, we propose the new color image segmentation algorithm using clustering method in the normalized r,g,b coordinates. The number of intrinsic clusters which are included in color image is estimated by the clustering quality measure and the initial centers of clusters are calculated by a hierarchical way. The proposed algorithm was varified by the computer simulation.

• Ocean Systems Engineering
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• v.2 no.2
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.569-574
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• 2003

Computer vision system is broadly adapted like as autonomous vehicle system, product line inspection, etc., because it has merits which can deal with environment flexibly. However, for applying it for that industry, it has to clear the problem that recognize position parameter of itself. So that computer vision system stands in need of camera calibration to solve that. Camera calibration consists of the intrinsic parameter which describe electrical and optical characteristics and the extrinsic parameter which express the pose and the position of camera. And these parameters have to be reorganized as the environment changes. In traditional methods, however, camera calibration was achieved at off-line condition so that estimation of parameters is in need again. In this paper, we propose a method to the calibration of camera using line correspondence in image sequence varied environment. This method complements the corresponding errors of the point corresponding method statistically by the extraction of line. The line corresponding method is strong by varying environment. Experimental results show that the error of parameter estimated is within 1% and those is effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• Korean Journal of Agricultural Science
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• v.44 no.2
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• pp.283-295
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• 2017

This study analyzed the effect of the intrinsic and extrinsic attributes of gochujang, Korean red chili paste, on purchasing intention and recommendation intention for consumption. Survey participants were female, married, aged 30 - 39 years, and highly educated with graduation from a university. Most participants purchased gochujang 1 - 2 times per year, most commonly at a shopping mall, and acquired information on the gochujang product from an advertisement or sponsored TV shows. For the factor analysis, five variables for intrinsic quality were considered: namely, healthiness, economics, convenience, diversity, and sense, whereas three variables were considered for extrinsic quality: trust, external appearance, and image. The factor analysis also confirmed the correlation between the validity and the reliability of the purchasing and recommendation intentions. The effect of intrinsic quality of gochujang on purchasing and recommendation intentions was tested through a multiple regression analysis. The purchase intention was most significantly affected by healthiness, cost, and convenience. On the other hand, the recommendation intention was most significantly affected by the diversity and, to a lesser degree, by the healthiness of the product. Among the extrinsic qualities, trust of consumers and the product appearance had a significant effect on purchasing intention. Recommendation intention was significantly affected by the appearance. And trust significantly influenced the recommendation. Therefore, a concrete and systematic marketing approach considering these factors.

• Fashion & Textile Research Journal
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• v.9 no.2
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• pp.197-202
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• 2007

The femme fatale image presently observable in various fields is reproducing its image through repetitive imitation, change and application, in particular, through 'movies' which have a greater ripple effect on the public than any other mass media by incessantly producing a countless number of images. This study aims to figure out the intrinsic meaning and the characteristics of the image of femme fatale, understand the modern expression of it in movies and finally shed light on its image represented in Korean movies. For this study, the literature and internet materials related to the image of femme fatale in the movie "Sympathy for Lady Vengeance" and the general concept of femme fatale were comprehensively surveyed. The femme fatale image which is represented in this movie is classified into 4 images ; disguise & mystery, retribution & cruelty, enchantment & beauty, salvation & redemption. The findings of this study provide an insight into how the femme fatale image is expressed in movies, the mass media which has a gigantic ripple effect, and provide the momentum to recognize the need and significance of understanding the femme fatale image represented in Korean movies.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.171-176
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• 2004

Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2748-2766
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• 2016

Compared with traditional patch-based sparse representation, recent studies have concluded that group-based sparse representation (GSR) can simultaneously enforce the intrinsic local sparsity and nonlocal self-similarity of images within a unified framework. This article investigates an accelerated split Bregman method (SBM) that is based on GSR which exploits image compressive sensing (CS). The computational efficiency of accelerated SBM for the measurement matrix of a partial Fourier matrix can be further improved by the introduction of a fast Fourier transform (FFT) to derive the enhanced algorithm. In addition, we provide convergence analysis for the proposed method. Experimental results demonstrate that accelerated SBM is potentially faster than some existing image CS reconstruction methods.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.385-392
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• 2013

An uncalibrated visual servo control method for tracking a target is presented. We define the robot-positioning problem as an unconstrained optimization problem to minimize the image error between the target feature and the robot end-effector feature. We propose a method to find the residual term for more precise modeling using the secant approximation method. The composite image Jacobian is estimated by the proper method for eye-to-hand configuration without knowledge of the kinematic structure, imaging geometry and intrinsic parameter of camera. This method is independent of the motion of a target feature. The algorithm for regulation of the joint velocity for safety and stability is presented using the cost function. Adaptive regulation for visibility constraints is proposed using the adaptive parameter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.972-978
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• 2009

In order to achieve color constancy, this paper proposes a method that can detect an invariant direction that affects formation of an intrinsic image significantly, using eigenvector in the $\chi$-chromaticity space. Firstly, image is converted into datum in the $\chi$-chromaticity space which was suggested by Finlayson et al. Secondly, it removes datum, like noises, with low probabilities that may affect an invariant direction. Thirdly, so as to detect the invariant direction that is consistent with a principal direction, the eigenvector corresponding to the largest eigenvalue is calculated from datum extracted above. Finally, an intrinsic image is acquired by recovering datum with the detected invariant direction. Test images were used as parts of the image data presented by Barnard et al., and detection performance of invariant direction was compared with that of entropy minimization method. The results of experiment showed that our method detected constant invariant direction since the proposed method had lower standard deviation than the entropy method, and was over three times faster than the compared method in the aspect of detection speed.