• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.39-46
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• 2019

This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.181-197
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• 2001

A heuristic method TABU-CSP using Tabu Search (TS) is described for solving Constraint Satisfaction Problems (CSPs). The method is started with a complete but inconsistent solution of a binary CSP and obtained in prespecified number of iterations either a consistent solution or a near optimal solution with an acceptable number of conflicts. The repair in the solution at each iterative step is done by using two heuristics alternatively. The first heuristic is a min-conflicts heuristic that chooses a variable with the maximum number of conflicts and reassigns it the value which leads to the minimum number of conflicts. If the acceptable solution is not reached after the search continued for a certain number of iterations, the min-conflict heuristic is changed and the variable selected least number of times is chosen for repair. If an acceptable solution is not reached, the method switches back to the min-conflict heuristic and proceeds further. This allowed the method to explore a different region of search space space for the solution as well as to prevent cycling. The demonstration of the method is shown on a toy problem [9]which has no solution. The method is then tested on various randomly generated CSPs with different starting solutions. The performance of the proposed method in terms of the average number of consistency is checked and the average number of conflicts is conflicts is compared with that of the Branch and Bound(BB) method used to obtain the same solution. In almost all cases, the proposed method moves faster to the acceptable solution than BB.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.21-24
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• 2001

In this paper, we present a fast face detection algorithm by estimating the eye region using neural network. To implement a real time face detection system, it is necessary to reduce search space. We limit the search space just to a few pairs of eye candidates. For the selection of them, we first isolate possible eye regions in the fast and robust way by modified histogram equalization. The eye candidates are paired to form an eye pair and each of the eye pair is estimated how close it is to a true eye pair in two aspects : One is how similar the two eye candidates are in shape and the other is how close each of them is to a true eye image A multi-layer perceptron neural network is used to find the eye candidate region's closeness to the true eye image. Just a few best candidates are then verified by eigenfaces. The experimental results show that this approach is fast and reliable. We achieved 94% detection rate with average 0.1 sec Processing time in Pentium III PC in the experiment on 424 gray scale images from MIT, Yale, and Yonsei databases.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.487-496
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• 2003

The promoter that plays a very important role in gene expression as a signal part has various binding sites for transcription factors. These binding sites are located on various parts in promoter region and have highly conserved consensus sequence patterns. This paper presents a new method for the consensus pattern search in promoter regions using genetic algorithm, which adopts the assumption of N-occurrence-per-dataset model of MEME algorithm and employs the advantage of Wataru method in determining the pattern length. Our method will be employed by genome researchers who try to predict the promoter region on anonymous DNA sequence and to find out the binding site for a specific transcription factor.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.645-650
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• 2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFARF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1584-1590
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• 2008

The combined query which consists of the region and trajectory query finds trajectories of moving objects which locate in a certain region. The trajectory query is very informant factor to determine query performance because it processes a point query continuously to find predecessors. This results in bad performance due to revisiting nodes in an index. This paper suggests an efficient method for the combined query based on the 3-dimensional R-tree which has good performance of the region query. The basic idea is that we define the least common search line which enables to search single path and a filtering method based on prediction without revisiting nodes.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.651-659
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• 2000

It is very important to extract the heart region in the medical images. In this paper, we present the automatic heart region extraction in the EBT (electron beam tomography) images. We use contrast thresholding, anatomic knowledge, and mathematical morphology to extract the heart region. Using these results, we applied the active contour models (snakes) to search the exact region. We analyzed the experimental results by comparing the results with the results made by medical experts.

• Journal of Acupuncture Research
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• v.34 no.3
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• pp.91-100
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• 2017

Objectives : We conducted a literature search to identify trends with respect to miniscalpel acupuncture points (MAPs) of the cervical region with the aim of providing guidance regarding miniscalpel acupuncture (MA) in the cervical region. Methods : We searched 2 overseas sites (PubMed and Google Scholar) and 5 domestic sites (NDSL, RISS, KISS, OASIS and Korean Traditional Knowledge Portal) for clinical trials of MA of the cervical region. The search terms used were "acupotomy or miniscalpel acupuncture or miniscalpel" and "cervical." Of 73 studies found, 11 were included in this review, 6 of which presented exact MAPs. Owing to the lack of data, we refer to 1 Korean and 4 Chinese articles to analyze the exact location and meaning of the MAPs used in the published studies and to propose other clinically applicable MAPs. Results : We identified 10 of the most commonly used MAPs in the published studies, including those located below the external occipital protuberance, 2-2.5 cm both side down of the external occipital protuberance, 4.5-5 cm both side down of the external occipital protuberance and C3-7 spinous process. Furthermore, we proposed 13 additional MAPs that can be used clinically. Conclusion : We hope that this study will form a basis for the development of MA and hope to improve the safety and reproducibility in future MA studies of the cervical region.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.102-111
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• 1999

In this paper, we propose a fast full search block matching algorithm using the search region subsampling and the difference of adjacent pixels in current block. In the proposed algorithm, we calculate the lower bound of mean absolute difference (MAD) at each search point using the MAD value of neighbor search point and the difference of adjacent pixels in current block. After that, we perform block matching process only at the search points that need block matching process using the lower bound of MAD at each search point. To calculate the lower bound of MAD at each search point, we need the MAD value of neighbor search point. Therefore, the search points are subsampled at the factor of 4 and the MAD value at the subsampled search points are calculated by the block matching process. And then, the lower bound of MAD at the rest search points are calculated using the MAD value of the neighbor subsampled search point and the difference of adjacent pixels in current block. Finally, we discard the search points that have the lower bound of MAD value exceed the reference MAD which is the minimum MAD value of the MAD values at the subsampled search points and we perform the block matching process only at the search points that need block matching process. By doing so, we can reduce the computation complexity drastically while the motion compensated error performance is kept the same as that of full search block matching algorithm (FSBMA). The experimental results show that the proposed method has a much lower computational complexity than that of FSBMA while the motion compensated error performance of the proposed method is kept same as that of FSBMA.

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.