• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.168-175
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• 2013

Color consistency in stereoscopic contents is important for 3D display systems. Even with a stereo camera of the same model and with the same hardware settings, complex color discrepancies occur when acquiring high quality stereo images. In this paper, we propose an integrated color matching method that use cumulative histogram in global matching and estimated 3D-distance for the stage of local matching. The distance between the current pixel and the target local region is computed using depth information and the spatial distance in the 2D image plane. The 3D-distance is then used to determine the similarity between the current pixel and the target local region. The overall algorithm is described as follow; First, the cumulative histogram matching is introduced for reducing global color discrepancies. Then, the proposed local color matching is established for reducing local discrepancies. Finally, a weight-based combination of global and local matching is computed. Experimental results show the proposed algorithm has improved global and local error correction performance for stereoscopic contents with respect to other approaches.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.537-543
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• 2015

Liquid crystal displays (LCDs) have slow responses, so motion blurs are often perceived in fast moving scenes. To reduce this motion blur, we propose a novel method of robust motion compensated frame interpolation (MCFI) based on bidirectional motion estimation (BME) and weight-overlapped block motion compensation (WOBMC) with variable block sizes. In most MCFI methods, a static block size is used, so some block artefacts and motion blurs are observed. However, the proposed method adjusts motion block sizes and search ranges by comparing matching scores, so the precise motion vectors can be estimated in accordance with motions. In the MCFI, overlapping ranges for WOBMC are also determined by adjusted block sizes, so the accurate MCFI can be performed. In the experimental results, the proposed method strongly reduced motion blurs arisen from large motions, and yielded interpolated images with high visual performance and peak signal-to-noise ratio (PSNR).

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.253-258
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• 2003

We consider the problem of grouping orders into lots. The problem is modelled by a graph G=(V,E), where each node ${\nu}{\in}V$ denotes order specification and its weight ${\omega}(\nu)$ the orders on hand for the specification. We can construct a lot simply from orders of single specification. For a set of nodes (specifications) ${\theta}{\subseteq}V$, if the distance of any two nodes in $\theta$ is at most d, it is also possible to make a lot using orders on the nodes. The objective is to maximize the number of lots with size exactly $\lambda$. In this paper, we prove that our problem is NP-Complete when $d=2,{\lambda}=3$ and each weight is 0 or 1. Moreover, it is also shown to be NP-Complete when $d=1,{\lambda}=3$ and each weight is 1,2 or 3.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.29-34
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• 2001

In this paper, a new associative memory system for analog time-sequential data processing is proposed. This system effectively associate time-sequential data using not only matching with present data but also matching with past data. Furthermore in order to improve error correction ability, weight varying in time domain is introduced in this system. The network is simulated with several periodic time-sequential input patterns including noise. The results show that the proposed system has ability to correct input errors. We expect that the proposed system may be applied for a real time processing of analog time-sequential information.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1474-1482
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• 2004

In this paper, we propose an approach for extracting and filtering block motion vectors using an adaptive weight function. We first extract motion vectors from a sequence of images by using size-varibale block matching and then process them by adaptive robust estimation to filter out outliers (motion vectors out of concern). The proposed adaptive robust estimation defines a continuous sigmoid weight function. It then adaptively tunes the sigmoid function to its hard-limit as the residual errors between the model and input data are decreased, so that we can effectively separate non-outliers (motion vectors of concern) from outliers with the finally tuned hard-limit of the weight function. The experimental results show that the suggested approach is very effective in filtering block motion vectors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.49-55
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• 2013

In this paper, we proposed a good classifier to match different spatial data sets by applying evaluation of classifiers performance in data mining and biometrics. For this, we calculated distances between a pair of candidate features for matching criteria, and normalized the distances by Min-Max method and Tanh (TH) method. We defined classifiers that shape similarity is derived from fusion of these similarities by CRiteria Importance Through Intercriteria correlation (CRITIC) method, Matcher Weighting method and Simple Sum (SS) method. As results of evaluation of classifiers performance by Precision-Recall (PR) curve and area under the PR curve (AUC-PR), we confirmed that value of AUC-PR in a classifier of TH normalization and SS method is 0.893 and the value is the highest. Therefore, to match different spatial data sets, we thought that it is appropriate to a classifier that distances of matching criteria are normalized by TH method and shape similarity is calculated by SS method.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.95-116
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• 2009

Ontologies have provided supports in integrating heterogeneous and distributed information. More and more ontologies and tools have been developed in various domains. However, building ontologies requires much time and effort. Therefore, ontologies need to be shared and reused among users. Specifically, finding the desired ontology from an ontology repository will benefit users. In the past, most of the studies on retrieving and ranking ontologies have mainly focused on lexical level supports. In those cases, it is impossible to find an ontology that includes concepts that users want to use at the semantic level. Most ontology libraries and ontology search engines have not provided semantic matching capability. Retrieving an ontology that users want to use requires a new ontology selection and ranking mechanism based on semantic similarity matching. We propose an ontology selection and ranking model consisting of selection criteria and metrics which are enhanced in semantic matching capabilities. The model we propose presents two novel features different from the previous research models. First, it enhances the ontology selection and ranking method practically and effectively by enabling semantic matching of taxonomy or relational linkage between concepts. Second, it identifies what measures should be used to rank ontologies in the given context and what weight should be assigned to each selection measure.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.164-174
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• 2015

In a real scenario, radiometric change has frequently occurred in the stereo image acquisition process using multiple cameras with geometric characteristics or moving a single camera because it has different camera parameters and illumination change. Conventional stereo matching algorithms have a difficulty in finding correct corresponding points because it is assumed that corresponding pixels have similar color values. In this paper, we present a new method based on the local descriptor reflecting intensity, gradient and texture information. Furthermore, an adaptive weight for local descriptor based on the entropy is applied to estimate correct corresponding points under radiometric variation. The proposed method is tested on Middlebury datasets with radiometric changes, and compared with state-of-the-art algorithms. Experimental result shows that the proposed scheme outperforms other comparison algorithms around 5% less matching error on average.

• Journal of Korean Academy of Nursing
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• v.36 no.8
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• pp.1331-1339
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• 2006

Purpose. The purpose of this study was to test the effects of infant massage (auditory (mother's voice), tactile/ kinesthetic (massage) and visual (eye to eye contact) stimulation) on weight and height of infant and mother-infant interaction with normal infants over a period of 4 weeks. Method. This study was designed as a nonequivalent control group pretest-posttest design. The experimental group infants (aged 2-6 months) participated in one of the infant massage programs at the health district center for 4 weeks. The control group (N=26) was paired with the experimental group (N=26) by matching the infant's age and sex. Infant weight, height, and mother-infant interaction were measured two times and recordings of the mother-infant interaction were done using the video equipment in a room at the health center for 10 minutes. Results. After 4 weeks of massage, there were no significant differences weight gain and height increase between the two groups. Comparison of the total scores for the mother-infant interaction between the two groups showed a significant difference (t=5.21, p=.000). There were also significant differences on maternal response (t=3.78, p=000), infant response (t=5.71, p=000) and dyadic response (t=4.05, p=000) in the mother-infant interaction between the two groups. Conclusion. Overall, the results of this study reassure that infant massage facilitates the mother-infant interaction for infants and mothers who give massage to their baby.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.279-284
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• 2017

The visual impact of fonts on lots of documents and design work is significant. Accordingly, the users desire to appropriately use fonts suitable for their intention. However, existing font recommendation programs are difficult to consider what users want. Therefore, we propose a font recommendation system based on user-evaluated font attribute value. The properties of a font are called attributes. In this paper, we propose a font recommendation module that recommends a user 's desired font using the attributes of the font. In addition, we classify each attribute into three types of usage, personality, and shape, suggesting the font that is closest to the desired font, and suggest an optimal font recommendation algorithm. In addition, weights can be set for each use, personality, and shape category to increase the weight of each category, and when a weight is used, a more suitable font can be recommended to the user.