• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.7-15
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• 2014

This paper proposed a recognition algorithm of human facial expressions using the PCA and the template matching. Firstly, face image is acquired using the Haar-like feature mask from an input image. The face image is divided into two images. One is the upper image including eye and eyebrow. The other is the lower image including mouth and jaw. The extraction of facial components, such as eye and mouth, begins getting eye image and mouth image. Then an eigenface is produced by the PCA training process with learning images. An eigeneye and an eigenmouth are produced from the eigenface. The eye image is obtained by the template matching the upper image with the eigeneye, and the mouth image is obtained by the template matching the lower image with the eigenmouth. The face recognition uses geometrical properties of the eye and mouth. The simulation results show that the proposed method has superior extraction ratio rather than previous results; the extraction ratio of mouth image is particularly reached to 99%. The face recognition system using the proposed method shows that recognition ratio is greater than 80% about three facial expressions, which are fright, being angered, happiness.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.100-107
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• 2012

Recently the need for advanced security technologies are increasing as the occurrence of intelligent crime is growing fastly. Previous methods for face disguise detection are required for the improvement of accuracy in order to be put to practical use. In this paper, we propose a new disguise detection method using the template matching and Adaboost algorithm. The proposed system detects eyes based on multi-scale Gabor feature vector in the first stage, and uses template matching technique in oreder to increase the detection accuracy in the second stage. The template matching plays a role in determining whether or not the person of the captured image has sunglasses on. Adaboost algorithm is used to determine whether or not the person of the captured image wears a mask. Experimental results indicate that the proposed method is superior to the previous methods in the detection accuracy of disguise faces.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.547-557
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• 2014

This paper presents a method for designing circular template used in similarity measurement for image registration. Circular template has translation and rotation invariant property, which results in correct matching of control points for image registration under the condition of translation and rotation between reference and sensed images. Circular template consisting of the pixels located on the multiple circumferences of the circles whose radii vary from zero to a certain distance, is converted to two-dimensional Discrete Polar Coordinate Matrix (DPCM), whose elements are the pixels of the circular template. For sensed image, the same type of circular template and DPCM are created by rotating the circular template repeatedly by a certain degree in the range between 0 and 360 degrees and then similarity is calculated using mutual information of the two DPCMs. The best match is determined when the mutual information for each rotation angle at each pixel in search area is maximum. The proposed algorithm was tested using KOMPSAT-2 images acquired at two different times and the results indicate high accurate matching performance under image rotation.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.461-472
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• 2005

In this paper, we propose face feature extraction algorithm through stereo image's matching value. The proposed algorithm detected face region by change the RGB color space of skin color information to the YCbCr color space. Applying eye-template from extracted face region geometrical feature vector of feature about distance and lean, nose and mouth between eye extracted. And, Proposed method could do feature of eyes, nose and mouth through stereo image's matching as well as 2D feature information extract. In the experiment, the proposed algorithm shows the consistency rate of 73% in distance within about 1m and the consistency rate of 52%in distance since about 1m.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.112-118
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• 2005

In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The proposed measure is obtained by binary-thresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is compared with the normalized covariance in terms of the classification ability of the successfulness of the locating markers. The proposed measure is evaluated for the scanned images of HPV DNA microarrays where the marker locating is a critical issue because of the small number of spots. The targeting spots of HPV DNA chips are designed for genotyping 22 types of the human papilloma virus(HPV). The proposed measure is proven to give more discriminative response reducing the miss cases of the successful marker locating.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.1-10
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• 2005

In this Paper, we propose a new block matching a1gorithm that extracts motion vectors from consecutive range data. The proposed method defines a matching metric that integrates intensity, hue, and range. Our algorithm begins matching with a small matching template. If the matching degree is not good enough, we slightly expand the size of a matching template and then repeat the matching process until our matching criterion is satisfied or the predetermined maximum size has been reached. As the iteration proceeds, we adaptively adjust weights of the matching metric by considering the importance of each feature. In the experiments, we show that our block matching approach can work as a promising solution by comparing the proposed method with previously known method in terms of performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.204-206
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• 2016

본 논문에서는 template matching을 이용한 PMMVD(Pattern Matched Motion Vector Derivation)기술에 대해 움직임 추정 방식에 따라 복잡도를 분석한다. PMMVD 기술은 HEVC의 화면 간 예측 기술과는 다르게 움직임과 관련된 정보를 부호화하지 않으며, 복호화기에서 움직임 벡터를 추정하는 방식이다. 따라서 종래의 기술 대비 높은 효율이 발생하지만 복호화기의 복잡도는 급격히 증가하게 된다. 이러한 이유로 다양한 움직임 추정 방식에 따라 성능을 분석하여 최적의 조합을 찾는 것은 매우 중요한 이슈임을 알 수 있다. 이를 위하여 현재 JVET(Joint Video Exploration Team)에서 FVC(Future Video Coding)를 위해 발표한 참조 소프트웨이인 JEM 2.0(Joint Exploration Test Model 2)을 이용하여 실험을 수행하고 향후 연구 방향을 논의한다.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.873-881
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• 2017

Prevention of drowsy driving is one of the important issues for safe driving. In this study, the algorithm for detection of drowsy driving has been developed. The algorithm was implemented by applying template matching and line profile, which detects eye blink. The accuracy of eye detection and blink detection was $97.45{\pm}3.67%$ and $98.50{\pm}0.92%$, which was resulted from the verification experiment that 21 subjects participated. Consequently, the algorithm is expected to be used to prevent sleep-deprived driving.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.306-309
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• 1996

This paper presents a method of landmark recognition in indoor environments using a neural-network for an autonomous mobile robot. In order to adapt to image deformation of a landmark resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The MLTM is. used for matching an image template with deformed real images and the DASM is proposed to detect correct feature points among incorrect feature points. Finally a feed-forward neural-network using back-propagation algorithm is adopted for recognizing the landmark.