• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.7-12
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• 2011

In this paper, we propose the technique detecting interest object region effectively in the images from periscope of submarine based on self-generated template. First, we extract the sea-sky line, and divide it into sky and sea area from background region based on the sea-sky line. In each divided background region, the blocks which can be represented in each background region are set as a reference template. After dividing an image into several same size of blocks, we apply multi template matching to the divided search blocks and histogram template to divide the image into object region and background region. Proposed algorithm is adapted to various images in which objects exist in the background of sea and sky. We verified that proposed algorithm performed properly without given informmed prby prior learning.ropso, regardless of the slope of sea-sky line and the locmed p of object based on sea-sky line, we verified that the objects region was segmented effectively from the input image.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.399-400
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• 2007

• Journal of KIBIM
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• v.10 no.4
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• pp.98-109
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• 2020

Based on the prior research which developed the consistency review checklist of the BIM model and 2D drawing through the drawing analysis of the construction documents phase, the apparent limits of the existing template and the template development items were derived. As well, the BIM-based drawing templates of the construction documentation phase were developed and verified using ArchiCAD BIM software. The developed template was then applied to the actual project model in the construction documents phase, and, as a result, 50% of existing work elements could be utilized as templates. This is an increase of more than 30% over the existing template utilization elements, and it is analyzed to be effective in practical application and utilization. Based on the results of this study, if the BIM model construction criteria matching the drawing's utilization purpose are presented, while at the same time the BIM data interlocking and drawing template development studies are conducted, the utilization of BIM data can be maximized and additional drawing work can be minimized to increase the percentage of template utilization elements. In addition, it is believed that this can employed to address functional and institutional problems of BIM-based drawing and make a contribution to the activation of BIM.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.85-93
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• 2008

For music score recognition, several approaches have been proposed including shape matching, statistical methods, neural network based methods and structural methods. In this paper, we deal with recognition for low resolution images which are captured by the digital camera of a mobile phone. Considerable distortions are included in these low resolution images, so when existing technology is used, many problems appear. First, captured images are not stable in the sense that they contain lots of distortions or non-uniform illumination changes. Therefore, notes or symbols in the music score are damaged and recognition process gets difficult. This paper presents recognition technology to overcome these problems. First, musical note to head, stick, tail part are separated. Then template matching on head part of musical note, and remainder part is applied. Experimental results show nearly 100% recognition rate for music scores with single musical notes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.803-810
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• 2003

This paper addresses an image processing technique for the human papillomavirus (HPV) DNA chip to discriminate whether the probes are hybridized with the target DNA. HPV DNA chip is designed to determine HPV gene-types by using DNA probes for 22 HPV types. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker- dot locations with a small variation attributable to the accuracy of the dotter and the scanner. The probes are quadruplicated to enhance diagnostic fidelity. frier knowledge including the marker relative distance and the replication information of probes is integrated into the template matching technique with normalized covariance measure. It was demonstrated that the employment of both of the prior knowledges can be accomplished by simply averaging the template matching measures over the positions of the markers and probes. The resulting proposed scheme yields stable marker locating and probe classification.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.413-422
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• 2013

In this paper, we propose a novel method for real-time lane detection that is robust for inclined roads and not require a camera parameter, the Inverse Perspective Transform of the image, and the proposed lane filter. After finding the vanishing point from the start frame of the image and storing the region surrounding the vanishing point as the Template Area(TA), our method predict the lanes by scanning toward the lower part from the vanishing point of the image and obtain the image removed the perspective effect using the Inverse Perspective Transform coefficients extracted based on the predicted lanes. To robustly determine lanes on inclined roads, the region surrounding the vanishing point is set up as the template area (TA), and, by recalculating the vanishing point by tracing the area similar to the TA (SA) in the input image through template matching, it responds to the changes on the road conditions. The proposed method for a more robust lane detection method for inclined roads is a lane detection method by applying a lane detection filter on an image removed of the perspective effect. Through this method, the processing region is reduced and the processing procedure is simplified to produce a satisfactory lane detection result of about 40 frames per second.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.55-58
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• 1997

In this paper, we study a signal processing method which extracts each MUAP(motor unit action potential) from EMG(Electromyogram) interference pattern or clinical diagnostic purposes. First of all, differential digital filtering is selected or eliminating the spike components of the MUAP's from the background noise. And, the algorithm identifies the spikes over the certanin threshold by template matching in frequency domain. After missing or false firing actor is cut off at the IPI(inter pulse interval) histogram, we averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and Finally, measures their amplitudes, durations, and numbers of phases. Specially, We introduce algorithm performed by template matching in the frequency domain. A typical 3-s signal recorded from the biceps brachii muscle using a conventional needle electrode during a isometric contraction is used. Finally, the method decomposed five simultaneous active MUAP's from original EMG signal.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.615-617
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• 1998

This paper proposes a new segmentation method of human races from grey scale images with clutter using a racial template and elliptical structure of the human head. Face detection technique can be applied in many areas of image processing such as face recognition, composition and computer graphics. Until now, many researches about face detection have been conducted, and applications in more complicated conditions are increasing. The general case is more in a complicated background than in a simple one, and a image with not only one face. Research and development of face detection in such a general case are growing rapidly, and the necessity for that is increasing continuously. Sirohey proposed a face detection method using linearized elliptical equation. The method designed in this paper is improved to be applicable even in the more general cases like where the face is much smaller than the image size and with many faces in one image using template matching and elliptic fitting technique.