• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.304-310
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• 2009

In this paper, target extraction method in FLIR(forward-looking infrared) images based on fuzzy thresholding which used bi-modality and adjacency to determine membership value is proposed. The bi-modality represents how a pixel is classified into a part of target using distribution of pixel values in a local region, and The adjacency is a measure to represent how each pixel is far from the target region. First, membership value is calculated using above two measures, and then fuzzy thresholding is performed to extract the target. To evaluate performance of proposed target extraction method, we compare other segmentation methods using various FLIR tank image. Experimental results show that the proposed algorithm is a good segmentation performance.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.77-86
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• 2008

The Web information sources can be regarded as the largest distributed database to the users. By virtually integrating the distributed information sources and regarding them as a single huge database, we can query the database to extract information. This capability is important to develop Web application programs. We have to infer a database schema from browsing-oriented Web documents in order to integrate databases. This paper presents a heuristic algorithm to infer the XML Schema fully automatically from semi-structured Web documents. The algorithm first extracts candidate pattern regions based on predefined structure-making tags, and determines a target pattern region using a few heuristic factors, and then derives XML Schema extraction rules from the target pattern region. The schema extraction rule is represented in XQuery, which makes development of various application systems possible using open standard XML tools. We also present the experimental results for several public web sources to show the effectiveness of the algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1411-1416
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• 2020

In this paper, we propose a method of extraction analysis of blood flow area on color doppler ultrasonography by using 4-directional contour tracking and K-Means algorithm. In the proposed method, ROI is extracted and a binarization method with maximum contrast as a threshold is applied to the extracted ROI. 4-directional contour algorithm is applied to extract the trapezoid shaped region which has blood flow area of brachial artery from the binarized ROI. K-Means based quantization is then applied to accurately extract the blood flow area of brachial artery from the trapezoid shaped region. In experiment, the proposed method successfully extracts the target area in 28 out of 30 cases (93.3%) with field expert's verification. And comparison analysis of proposed K-Means based blood flow area extraction on 30 color doppler ultrasonography and brachial artery blood flow ultrasonography provided by a specialist yielded a result of 94.27% accuracy on average.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.63-71
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• 2009

In this study, we propose a revised dynamic ROI (Region-of-Interest) coding method in which the focused ROI is automatically extracted without help from users during the recovery process of low DOF (Depth-of-Field) JPEG2000 image. The proposed method creates edge mask information using high frequency sub-band data on a specific level in DWT (Discrete Wavelet Transform), and then identifies the edge code block for a high-speed ROI extraction. The algorithm scans the edge mask data in four directions by the unit of code block and identifies the edge code block simply and fastly using a edge threshold. As the results of experimentation applying for Implicit method, the proposed method showed the superiority in the side of speed and quality comparing to the existing methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2352-2355
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• 2003

In recent yeas, studies on computer aided diagnosis (CAD) using image analysis on CT images have been conducted with respect to various diseases. Extracting ground-glass opacities (GGO) on lung CT images is one of such subjects, though it has not found an established method yet. If the region of ground-glass opacities is large on CT images, it can be detected without much difficulty. On the other hand, if the region is small, it is still difficult to find it exactly. In the latter case, increasing overlooking possibility cannot be avoided according to smaller size of the region. To solve this difficulty, this paper proposes an automatic technique for extracting ground-glass opacities on lung CT images employing some statistical parameters of a gray level histogram and a differential histogram. The proposed technique is applied to some lung CT images in the performed experiment. The results are shown with discussion on future work.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.14-19
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• 2001

This paper presents a new method of 3-D surface feature extraction using a quadratic pol expression. With a range image, we get an edge map through the modified scan line technique this edge map, we label a 3-dimensional object to divide object's region and extract cent corner points from it's region. Then we determine whether the segmented region is a planar or a curved from the quadric surface equation. we calculate the coefficients of the planar su the curved surface to represent regions. In this article. we prove performance of the metho synthetic and real (Odetics) range images.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2531-2542
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• 1997

This paper describes a method for region segmentation and string extractionin documents which are mixed with text, graphic and picture images by the use of the structural characteristic of connceted components. In segmentation of non-text regionas, with connection-characteristic functions which are made by structural characteristic of connected components, segmentation process is progressed. In the string extraction, first we organize basic-unit-region of which vertical and horizontal length are 1/4 of average length of connection components. Second, by merging the basic-unit-regions one other that have smaller values than a given connection intensity threshold. Third, by linking the word blocks with similar block anagles, initial strings are cresed. Finally the whold strings are generated by merging remaining word blocks whose angles are not decided, if their height and prosition are similar to the initial strings. This method can extract strings that are neither horizontal nor of various character sizes. Through computer exteriments with different style documents, we have shown that the feasibility of our method successes.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.94-99
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• 2008

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy C-means clustering algorithm is employed to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• The Journal of the Korean dental association
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• v.58 no.7
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• pp.398-403
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• 2020

Odontogenic anomalies can occur as a result of conjoining defects. These include fusion, gemination and concrescence. The presence of fused teeth can lead to various clinical problems, including the aplasia of permanent successor, the supernumerary teeth and delayed eruption of permanent teeth. In general, the supernumerary teeth associated with fusion is mainly found in the maxillary anterior region. This report describes rare cases of supernumerary tooth associated with fused teeth of mandibular primary lateral incisor and canine. In the first case, fused teeth was extracted. The supernumerary teeth was erupted at canine space. The second case is still being observed. Extraction of fused teeth and observation of supernumerary teeth is planned.