• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.800-808
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• 2008

A fingerprint verification system based on a set of invariant moment features and a nonlinear Back Propagation Neural Network(BPNN) verifier is proposed. An image-based method with invariant moment features for fingerprint verification is used to overcome the demerits of traditional minutiae-based methods and other image-based methods. The proposed system contains two stages: an off-line stage for template processing and an on-line stage for testing with input fingerprints. The system preprocesses fingerprints and reliably detects a unique reference point to determine a Region-of-Interest(ROI). A total of four sets of seven invariant moment features are extracted from four partitioned sub-images of an ROI. Matching between the feature vectors of a test fingerprint and those of a template fingerprint in the database is evaluated by a nonlinear BPNN and its performance is compared with other methods in terms of absolute distance as a similarity measure. The experimental results show that the proposed method with BPNN matching has a higher matching accuracy, while the method with absolute distance has a faster matching speed. Comparison results with other famous methods also show that the proposed method outperforms them in verification accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.308-314
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• 2006

A line scan camera is applied to enhance COG(Chip On Glass) inspection accuracy to be measured a few micro unit. The foreign substance detection among various faulty factors has been the most difficult technology in the faulty automatic inspection step since COG pattern is very miniature and complexity. In this paper, we proposed two step area segmentation template matching method to increase matching speed. Futhermore to detect foreign substance(such as dust, scratch) with a few micro unit, the new method using gradient mask and AND operation was proposed. The proposed 2 step template matching method increased 0.3 - 0.4 second matching speed compared with conventional correlation coefficient. Also, the proposed foreign substance applied masks enhanced $5-8\%$ faulty detection rate compared with conventional no mask application method.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.223-226
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• 2003

When we detect side-view face in color image, we decide a candidate face region using skin-tone color, and confirm to the face by template matching. Cang Wei use a left and a right template of face, calculate to similarity value by hausdorff method, and decide the final side-view face. It has a characteristic that side-view face is wide spreading neck region. To get exactly result, face region is separated vertically by 3 pixel unit, and matched template. In this paper, we assume that a side-view face is a right side-view or a left side-view face. We separate a half of the candidate face region vertically, and regard a left side as left candidate face, a right side as right candidate face by template matching. This method detect faster than Gang Wei method.

• Korean Journal of Computational Design and Engineering
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• v.12 no.4
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• pp.283-297
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• 2007

Seamless data integration in the CAx chain of the CAD/CAPP/CAM/CNC has been achieved to a high degree, but research concerning the transfer of data from conceptual sketches to a CAD system should be carried out further. This paper presents a method for reconstructing a 3D model from a freehand sketch. Sketch-based modeling research can be classified into gestural modeling methods and reconstructional modeling methods. This research involves the reconstructional modeling method. Here, Mitani's seminal work, designed for box-shaped 3D model using a predefined template, is improved by leveraging a relational template and specialized for automotive design. Matching between edge graphs of the relational template and the sketch is formulated and solved as the assignment problem using the feature vectors of the edges. Including the stroke preprocessing method required to generate an edge graph from a sketch, necessary procedures and relevant techniques for implementing the template-based modeling method are described. Examples from a working implementation are given.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.107-107
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• 2002

목적： I-123 IPT SPECT에서 striatum에 ROI를 설정하여 Strial Binding Ratio를 측정하기 위해 사용되는 육안적인 방법과 MR Template based Coregistration 방법을 비교 평가하였다. 대상 및 방법： 파킨슨씨병 환자(IPD) 15명(남/녀：8/7, 63.3$\pm$4.8세)과 정상인 8명(남/녀：2/6, 61.4$\pm$16.5세) 에서 I-123 IPT(259MBq)를 주사한 후 2시간에 SPECT 영상을 얻었고 미상핵과 조가비핵의 전, 후부 및 후두엽에 각각 육안적인 방법과 MR Template based Coregistration방법으로 ROI를 설정하였다. MR Template based Coregistration 방법은 MNI TIMR template을 이용하여 SPECT영상을 voxel based intensity matching 방법으로 coregistration한 후midthalamic level에서 striatum의 경계를 따라 설정된 ROI를 이용하였다. 육안적인 방법은 striatal uptake가 가장 높은 level에서 3개의 ROI template를 striatum에 위치하였다. 두 방법으로 SBR과 nnterior/posterior ratio of SBR(APR)를 측정하였고 정상인과 파킨슨씨병 환자에서 두 방법을 비교하였다.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.349-361
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• 2013

This paper proposes a fast face tracking method with only depth information. It is basically a template matching method, but it uses a early termination scheme and a sparse search scheme to reduce the execution time to solve the problem of a template matching method, large execution time. Also a refinement process with the neighboring pixels is incorporated to alleviate the tracking error. The depth change of the face being tracked is compensated by predicting the depth of the face and resizing the template. Also the search area is adjusted on the basis of the resized template. With home-made test sequences, the parameters to be used in face tracking are determined empirically. Then the proposed algorithm and the extracted parameters are applied to the other home-made test sequences and a MPEG multi-view test sequence. The experimental results showed that the average tracking error and the execution time for the home-made sequences by Kinect ($640{\times}480$) were about 3% and 2.45ms, while the MPEG test sequence ($1024{\times}768$) showed about 1% of tracking error and 7.46ms of execution time.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.217-222
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• 2017

Recent studies for working robot in dangerous places have been carried out on large unmanned ground vehicles or 4-legged robots with the advantage of long working time, but it is difficult to apply in practical dangerous fields which require the real-time system with high locomotion and capability of delicate working. This research shows the collaborated docking system of drone and ground vehicles which combines image processing algorithm and laser sensors for effective detection of docking markers, and is finally capable of moving a long distance and doing very delicate works. We proposed the docking system of drone and ground vehicles with sensor fusion which also suggests two template matching methods appropriate for this application. The system showed 95% docking success rate in 50 docking attempts.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.2
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• pp.165-173
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• 2012

Nationally, flatfish vaccination has been performed manually, and is a laborious and time-consuming procedure with low accuracy. The handling requirement also makes it prone to contamination. With a view to eliminating these drawbacks, we designed an automatic vaccine system in which the injection is delivered by a Cartesian coordinate robot guided by a vision system. The automatic vaccine injection system is driven by an injection site location algorithm that uses a template-matching technique. The proposed algorithm was designed to derive the time and possible angles of injection by comparing a search area with a template. The algorithm is able to vaccinate various sizes of flatfish, even when they are loaded at different angles. We validated the performance of the proposed algorithm by analyzing the injection error under randomly generated loading angles. The proposed algorithm allowed an injection rate of 2000 per hour on average. Vaccination of flatfish with a body length of up to 500mm was possible, even when the orientation of the fish was random. The injection errors in various sizes of flatfish were very small, ranging from 0 to 0.6mm.

• 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.