• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.533-535
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• 2003

The Euclidean distance is sensitive to the absolute offsets of time sequences, so it is not a suitable similarity measure in terms of shape. In this paper. we propose an indexing scheme for efficient matching and retrieval of time sequences based on the minimum distance. The minimum distance can give a better estimation of similarity in shape between two time sequences. Our indexing scheme can match time sequences of similar shapes irrespective of their vortical positions and guarantees no false dismissals

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.161-171
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• 2014

When the Hough transform is applied to identify an instance of a given model, the output is typically a histogram of votes cast by a set of image features into a parameter space. The next step is to threshold the histogram of counts to hypothesize a given match. The question is "What is a reasonable choice of the threshold?" In a standard implementation of the Hough transform, the threshold is selected heuristically, e.g., some fraction of the highest cell count. Setting the threshold too low can give rise to a false alarm of a given shape(Type I error). On the other hand, setting the threshold too high can result in mis-detection of a given shape(Type II error). In this paper, we derive two conditional probability functions of cell counts in the accumulator array of the generalized Hough transform(GHough), that can be used to select a scientific threshold at the peak detection stage of the Ghough.

• Genomics & Informatics
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• v.5 no.4
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• pp.143-151
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• 2007

To understand the mechanism of transcriptional regulation, it is essential to detect promoters and regulatory elements. Various kinds of methods have been introduced to improve the prediction accuracy of regulatory elements. Since there are few experimentally validated regulatory elements, previous studies have used criteria based solely on the level of scores over background sequences. However, selecting the detection criteria for different prediction methods is not feasible. Here, we studied the calibration of thresholds to improve regulatory element prediction. We predicted a regulatory element using MATCH, which is a powerful tool for transcription factor binding site (TFBS) detection. To increase the prediction accuracy, we used a regulatory potential (RP) score measuring the similarity of patterns in alignments to those in known regulatory regions. Next, we calibrated the thresholds to find relevant scores, increasing the true positives while decreasing possible false positives. By applying various thresholds, we compared predicted regulatory elements with validated regulatory elements from the Open Regulatory Annotation (ORegAnno) database. The predicted regulators by the selected threshold were validated through enrichment analysis of muscle-specific gene sets from the Tissue-Specific Transcripts and Genes (T-STAG) database. We found 14 known muscle-specific regulators with a less than a 5% false discovery rate (FDR) in a single TFBS analysis, as well as known transcription factor combinations in our combinatorial TFBS analysis.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.73-83
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• 2007

An information retrieval system, using exact match, needs preprocessing or query expansion to generate transliteration variants in order to search foreign word transliteration variants in the documents. This paper proposes an effective method to generate other transliteration variants from a given transliteration. Because simple rewriting of confused characters produces too many false variants, the proposed method controls the generation priority by learning confusion patterns from real uses and calculating their probability. Especially, the left and right context of a pattern is considered, and local rewriting probability and global rewriting probability are calculated to produce more probable variants in earlier stage. The experimental result showed that the method was very effective by showing more than 80% recall with top 20 generations for a transliteration variants set collected from KT SET 2.0.

• Journal of Biomedical Engineering Research
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• v.13 no.2
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• pp.165-174
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• 1992

Compliance mismatch across an end-to-end anastomosis was measured In the In vitro experimental setup. A 35mm camera was used and Image process was done in Gould/ DeAnza Image processor. The results showed that compliances of Penrose tubing and synthetic PTFE grafts were In good agreement with the previously reported In vivo data. PTFE grafts exhibited a nonlinear behavior with compliance decreasing with Increasing transmural pressure, whereas the compliance of the Penrose tubing remained relatively constant within the range of the pressures in which data were obtained. The lumen cross sections at the anastomosis were affected by the suture and the mismatch In compliance between the Penrose tubing and vascular grafts. The varla~lons In the lumen dtameter at the anastomosis was more pronounced with increasing transmural pressures. From the present study, it was clearly demonstrated that the compliance of prosthetic grafts Is much lower than that of the arteries. In addition to the hemodynamlc consequences, compliance mismatch across the anastomosis has been known to lead to Increased anastomotlc and suture stresses with resultant suture line dehlscence and false aneurysm formation. Thus, there are good hemodynamic reasons to suppose that Introduction of a less compliant arterial graft Into the arterial circulation wlll be damaging and that grafts should be made to match the elastic behavior of their host arteries as closely possible.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.74-86
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• 1994

In this paper a hierarchical stereo matching algorithm to obtain the disparity in wavelet transformed domain by using locally adaptive window and weights is proposed. The pyramidal structure obtained by wavelet transform is used to solve the loss of information which the conventional Gaussian or Laplacian pyramid have. The wavelet transformed images are decomposed into the blurred image the horizontal edges the vertical edges and the diagonal edges. The similarity between each wavelet channel of left and right image determines the relative importance of each primitive and make the algorithm perform the area-based and feature-based matching adaptively. The wavelet transform can extract the features that have the dense resolution as well as can avoid the duplication or loss of information. Meanwhile the variable window that needs to obtain precise and stable estimation of correspondense is decided adaptively from the disparities estimated in coarse resolution and LL(low-low) channel of wavelet transformed stereo image. Also a new relaxation algorithm that can reduce the false match without the blurring of the disparity edge is proposed. The experimental results for various images show that the proposed algorithm has good perfpormance even if the images used in experiments have the unfavorable conditions.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.17-31
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• 2017

The aim of the paper is to present an object recognition method toward augmented reality system that utilizes existing education instruments that was designed without any consideration on image processing and recognition. The light reflection, sizes, shapes, and color range of the existing target education instruments are major hurdles to our object recognition. In addition, the real-time performance requirements on embedded devices and user experience constraints for children users are quite challenging issues to be solved for our image processing and object recognition approach. In order to meet these requirements we employed a method cascading light-weight weak classification methods that are complimentary each other to make a resultant complicated and highly accurate object classifier toward practically reasonable precision ratio. We implemented the proposed method and tested the performance by video with more than 11,700 frames of actual playing scenario. The experimental result showed 0.54% miss ratio and 1.35% false hit ratio.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.385-392
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• 2016

Market analysis for a business plain is required for the success in the modern world. Most important part in this analysis is pedestrian traffic counting. A traditional way for this is counting it in person. However, it causes high labor costs and mistakes. This paper proposes an automatic algorithm to measure the pedestrian traffic count using images with webcam. The proposed algorithm is composed of two parts: pedestrian area detection and movement tracking. In pedestrian area detection, moving blobs are extracted and pedestrian areas are detected using HoG features and Adaboost algorithm. In movement tracking, multi-level matching and false positive removal are applied to track pedestrian areas and count the pedestrian traffic. Multi-level matching is composed of 3 steps: (1) the similarity calculation between HoG area, (2) the similarity calculation of the estimated position with Kalman filtering, and (3) the similarity calculation of moving blobs in the pedestrian area detection. False positive removal is to remove invalid pedestrian area. To analyze the performance of the proposed algorithm, a comparison is performed with the previous human area detection and tracking algorithm. The proposed algorithm achieves 83.6% accuracy in the pedestrian traffic counting, which is better than the previous algorithm over 11%.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.101-107
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• 2013

Generally the commercial high-resolution images have their coordinates, but the locations are locally different according to the pose of sensors at the acquisition time and relief displacement of terrain. Therefore, a process of image co-registration has to be applied to use the multi-temporal images together. However, co-registration is interrupted especially when images include the cloud-covered regions because of the difficulties of extracting matching points and lots of false-matched points. This paper proposes an automatic co-registration method for the cloud-covered high-resolution images. A scale-invariant feature transform (SIFT), which is one of the representative feature-based matching method, is used, and only features of the target (cloud-covered) images within a circular buffer from each feature of reference image are used for the candidate of the matching process. Study sites composed of multi-temporal KOMPSAT-2 images including cloud-covered regions were employed to apply the proposed algorithm. The result showed that the proposed method presented a higher correct-match rate than original SIFT method and acceptable registration accuracies in all sites.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.23-29
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• 2004

In this paper, we propose a search method for time sequences which supports the normalized distance as a similarity measure. In many applications where the shape of the time sequence is a major consideration, the normalized distance is a more suitable similarity measure than the simple Lp distance. To support normalized distance queries, most of the previous work has the preprocessing step for vertical shifting which normalizes each sequence by its mean. The proposed method is motivated by the property of sequence for feature extraction. That is, the variation between two adjacent elements of a time sequence is invariant under vertical shifting. The extracted feature is indexed by the spatial access method such as R-tree. The proposed method can match time series of similar shape without vertical shifting and guarantees no false dismissals. The experiments are performed on real data(stock price movement) to verify the performance of the proposed method.