• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.373-385
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• 2022

Due to the lack of information, medical tourists are regarded to be at high risk. Prior medical tourism research has found that various types of perceived risks have a significant impact on medical tourists' purchase behavior. Even though medical tourism is predicted to increase, there is a lack of behavioral research to explain how perceived risks affect medical tourists' purchase behavior. In the context of Korean medical tourism, this study attempts to evaluate the effects of multi-level (macro, organizational, and personal) factors on medical tourists' perceived risks and purchase intentions. A conceptual model and hypotheses were built and empirically validated to investigate links between multi-level characteristics, perceived risks, and purchasing intentions. The data for this study was collected from Chinese tourists using a questionnaire. The impact of cognitive country image, affective country image, and medical service quality on fundamental risk is confirmed by statistical testing. Surprisingly, expectancy discrepancy risk is influenced only by cognitive country image and information search capabilities. Both fundamental and expectation discrepancy risks lower medical tourists' purchase intentions. The findings of this study show that a multi-level strategy is required to investigate the links between perceived risks and medical tourism purchasing intentions based on macro, organizational, and personal factors.

• Journal of the Korean Society for information Management
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• v.25 no.2
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• pp.25-48
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• 2008

The purpose of this study is to suggest retrieval interfaces for Korean paintings which support users to retrieve specific digitalized images of them through various access points and to widely browse based on unique features Korean paintings. The study, first, develops a set of descriptive elements suitable for Korean Paintings. Twenty-six core elements and one hundred seventy-two attributes are selected as descriptive items for Korean paintings based on the opinion of 8 experts. Then, to gam realistic evidence of what descriptive elements of image serve users as access points, it is investigated which elements are used as retrieval access points among 26 core elements by 300 peered users who are consisted with two groups such as common users and domain specialists. The study, in final, designs two(general and advanced) types of search interfaces and display interfaces based on the most popular top 15 descriptive elements. This access-enhanced platform which enables user-oriented searches will satisfy users in image retrieving.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.13-22
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• 2004

With the proliferation of multimedia data, there is an increasing need to support the indexing and retrieval of high-dimensional image data. Although there have been many efforts, the performance of existing multidimensional indexing methods is not satisfactory in high dimensions. Thus the dimensionality reduction and the approximate solution methods were tried to deal with the so-called dimensionality curse. But these methods are inevitably accompanied by the loss of precision of query results. Therefore, recently, the vector approximation-based methods such as the VA- file and the LPC-file were developed to preserve the precision of query results. However, the performance of the vector approximation-based methods depend largely on the size of the approximation file and they lose the advantages of the multidimensional indexing methods that prune much search space. In this paper, we propose a new index structure called the GC-tree for efficient similarity search in image databases. The GC-tree is based on a special subspace partitioning strategy which is optimized for clustered high-dimensional images. It adaptively partitions the data space based on a density function and dynamically constructs an index structure. The resultant index structure adapts well to the strongly clustered distribution of high-dimensional images.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.17-24
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• 2005

In this paper, we will show that a control search methodology is a alternative method of a sequential search which is difficult in finding books for arrangement at library or a bookstore when books are out of place. To solve the problem of the sequential search, we apply a edge operator and the Hough Transform to boundary of a taken photograph image book. We generate histogram by a projected image from boundary range of selected books and select title areas from this and possible areas which are a character number of title, authors, a publishing company and an array sequence. Finally, we can select the final possible area of a book location by a curve fitting and a regression line extraction, and show utility through experiment.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.949-955
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• 2005

In this Paper, we propose fast block matching algorithm by dividing complex areas based on complexity order of reference block and square sub-block to reduce an amount of computation of full starch(FS) algorithm for fast motion estimation, while keeping the same prediction quality compared with the full search algorithm. By using the fact that matching error is proportional to the gradient of reference block, we reduced unnecessary computations with square sub-block adaptive matching scan based image complexity instead of conventional sequential matching scan and row/column based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination(PDE) algorithm without any prediction quality, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• Korean Institute of Interior Design Journal
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• v.26 no.2
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• pp.22-32
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• 2017

This research is to analyze the spatial information search features which shown by Eye fixation and movement and conducted eye tracking experiment for targeting sports shop spatial images which it are same but looks different. This is able to find out the eye movement feature according to placement of goods from the eye movement and movement distance of spatial visitor, and the result can be defined as following. First, the whole original-reverse left / right images have a higher number of observations in the [IN] area than in the [OUT] area. This is because after eye taking high observations in LA area of [IN] have been jump-over [OUT], performed search activities in low eye fixation without high eye fixation. Second, there was a difference in the frequency of the observation data as the composition of the images changed. The original image has been often fixed the eyes in LA area, and the one that has been observed for a long time is reverse left / right image. Also, fixation point was shown higher at the reverse left / right image as jump-over from [OUT] area to [IN] area. If LA area seen as reverse left / right image, it is located in right-hand side. The case where the dominant area is on the right side has a characteristic that the eye fixation is longer. This can be understand that the arrangement of products for attract the customer's attention in the commercial space might be more effective when it is on the right side. Third, the moving distance(IN ${\rightarrow}$ OUT) of the sight pointed to external from LA area was long in the both original-reverse left / right images, but it is no relation with search direction([IN${\rightarrow}$OUT] [IN${\rightarrow}$OUT]) of the sight. In other words, the sight that entered in LA area can be seen as visual perception activity for re-searching after big jump-over, in the case go in to outward (OUT area) after searching for more than certain time. The fact that the moving distance of eye is relatively short in the [IN ${\rightarrow}$ OUT] process considered as that the gaze that stays outside the LA area naturally enters in to LA area.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.926-930
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• 2006

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.158-165
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• 2018

Since a large amount of multimedia image has dramatically increased, it is important to search semantically relevant image. Thus, several semantic image annotation methods using RDF(Resource Description Framework) model in mobile environment are introduced. Earlier studies on annotating image semantically focused on both the image tag and the context-aware information such as temporal and spatial data. However, in order to fully express their semantics of image, we need more annotations which are described in RDF model. In this paper, we propose an annotation method inferencing with RDFS entailment rules and user defined rules. Our approach implemented in Moment system shows that it can more fully represent the semantics of image with more annotation triples.

• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.33-38
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• 2013

Image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes an efficient image descriptor which uses a local color and texture in the non-overlapped block images. To evaluate the performance of the proposed method, we assessed the retrieval efficiency in terms of ANMRR with common image dataset. The experimental trials revealed that the proposed algorithm exhibited a significant improvement in ANMRR, compared to Dominant Color Descriptor and Edge Histogram Descriptor.