• Journal of Mechanical Science and Technology
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• v.14 no.5
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• pp.518-529
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• 2000

A detailed and thorough parametric study of digital image correlation method is presented. A theoretical background and development of the method were introduced and the effects of various parameters on the determination of displacement outputs from the raw original and deformed image information were examined. Use of the normalized correlation coefficient, the use of 20 to 40 pixels for a searching window side, 6 variables searching, bi-cubic spline sub pixel interpolations and the use of coarse-fine search are some of the key choices among the results of parametric studies. The displacement outputs can be further processed with two dimensional curve fitting for the data noise reduction as well as displacement gradient calculation.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.411-417
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• 2015

To distinguish between HCC and HH is one of the important test methods in determining the treatment method by determining the treatment method by distinguishing malignant growth and benign tumors in liver CT scan. Currently, the specialist is reading CT images by their subjective judgment. So, the purpose of this study is to treat reading the CT images even more objective way. The test times after injection contrast medium in this study are the before injection phase(Pre.), artery phase(35sec), portal phase(70sec) and delay phase(180sec). The general pattern change of HCC in change of contrast enhancement pattern shows 26.6% matching. And the case of HH shows 16.6% matching. In order to observe the change of HU value between HCC and HH, each average values and standard deviation was confirm and as a result, it shows the lagre difference between artery and portal phase in lesion.(HCC$19.76{\pm}23.52$, HH$60.23{\pm}29.43$). And it shows the 76.6% matching in HCC and 80.0% matching in HH. Thorough this study, to suggest a HU value as objective analysis method and if the anlaysis method was used in clinical will assist in the diagnosis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.96-102
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• 2003

Video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching. This paper proposes two new sequence matching techniques for copy detection and compares the performance with color techniques that is the existing techniques. Motion, intensity and color-based signatures are compared in the context of copy detection. Comparison of experimental results are reported on detecting copies of movie clips.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.69-77
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• 1992

Pattern Recognition is one of the fundamental areas of computer vision. The recognition of patterns with varying size and severe defects is especially important. However, it is known that the conventional algorithms such as GHT or structural approaches have limitations in speed and accuracy. In this paper, in order to avoid above-mentioned problems, we propose a new recognition algorithm which exploits the histogram of contour directions and the sampled spot matching method. While the former provides little influence against size variation, the latter has strong immunity to noise and defects. We applied those proposed algorithms for the recognition of numbers extracted from the car number plates and shapes of aircraft. Experimental result shows that it is possible to solve above-mentioned problems by complementary uses of those two suggested algorithms. The contour directional histogram method resulted in high-speed of average 0.013 sec/char and 0.1 sec/aircraft-image on IBM-386. The accuracy of recognition is as high as 99%. Sampled spot matching method has less speed than the former one, however, it showed fairly strong immunity to noise and defects.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.39-45
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• 2017

Conventional Color-Based Face Recognition Methods are Sensitive to Illumination Changes, and there are the Possibilities of Forgery and Falsification so that it is Difficult to Apply to Various Industrial Fields. In This Paper, we propose a Face Recognition Method Based on LBP(Local Binary Pattern) using the Depth Images to Solve This Problem. Face Detection Method Using Depth Information and Feature Extraction and Matching Methods for Face Recognition are implemented, the Simulation Results show the Recognition Performance of the Proposed Method.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1073-1080
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• 2011

In this study, a target detection algorithm was proposed for using hyperspectral imagery. The proposed algorithm is designed to have minimal processing time, low false alarm rate, and flexible threshold selection. The target detection procedure can be divided into two steps. Initially, candidates of target pixel are extracted using matching ratio of spectral pattern that can be calculated by spectral derivation. Secondly, spectral distance is computed only for those candidates using Euclidean distance. The proposed two-step method showed lower false alarm rate than the Euclidean distance detector applied over the whole image. It also showed much lower processing time as compared to the Mahalanobis distance detector.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1135-1139
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• 1989

Three layered neural network was applied for the pattern recognition problem of human spermatozoa in clinical test. The goodness of recognition rate was studied in relation to the number of hidden layer cells and of output layer cells. The proposed method provided better results than conventional template matching technique. Parallel processing of the back propagation learning algorithm was also studied using transputers and its performance was evaluated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.653-655
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• 2001

본 논문은 홍채영상에 대한 에지를 검출하고 홍채진단을 위한 에지영상패턴 매칭을 이용하여 홍채의 진단영역을 인식하는 연구이다. 에지검출기법은 8방향 키어쉬-라프라시언 기법을 적용하고 진단영역인식은 진단기준패턴과 입력에지영상패턴과 오버레이 패턴매칭으로 진단영역을 인식하였다. 그 결과 적용한 에지검출영상의 PSNR이 131정도이며 패턴매칭 영역인식결과는 86%정도로 홍채에 의한 인체의 상태를 추정하는 자동진단시스템으로 환용 가능성을 제시하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.397-400
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• 2003

공장 현장에서 적용할 수 있는 산업용 비전 검사시스템의 개발을 위해서는 안정적이면서도 고속 패턴 정합이 가능한 알고리즘의 개발이 요구된다. 기존의 농담정규화상관(NGC)법을 사용하는 알고리즘은 과도한 계산량과 조명의 불안정에 영향을 많이 받는 문제점이 있다 본 논문에서는 영상 피라미드와 물체경계의 에지점들을 이용하여 기존 NGC 알고리즘의 단점을 보완하고 고속 패턴정합을 수행하는 에지기반 점상관 알고리즘을 제안하고 이를 실제 영상에 적용하여 그 신뢰성을 검증한다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.23-30
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• 2014

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.