• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.937-945
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• 2014

Multi-modal biometric system can use another biometric trait in the case of having deficiency at a biometric trait. It also has an advantage of improving the performance of personal identification by using multiple biometric traits, so studies on new biometric traits have continuously been performed. The inner face of finger is a relatively new biometric trait. It has two major features of knuckle lines and wrinkles, which can be used as discriminative features. This paper proposes a finger identification method based on displacement vector to effectively process some variation appeared in contactless hand image. At first, the proposed method produces displacement vectors, which are made by connecting corresponding points acquired by matching each pair of local block. It then recognize finger by measuring the similarity among all the detected displacement vectors. The experimental results using pubic CASIA hand image database show that the proposed method may be effectively applied to personal identification.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.57-60
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• 2000

This paper presents a new adaptive fast motion estimation algorithm along with its architecture. The conventional algorithm such as full - search algorithm, three step algorithm have some disadvantages which are related to the amount of computation, the quality of image and the implementation of hardware, the proposed algorithm uses spatial correlation and a slope of motion vector in order to reduce the amount of computation and preserve good image quality, The proposed algorithm is better than the conventional Block Matching Algorithm(BMA) with regard to the amount of computation and image quality. Also, we propose an efficient at chitecture to implement the proposed algorithm. It is suitable for real time processing application.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.203-207
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• 1996

This paper describes a method for estimating motion vectors in a video sequence. In this method, we find motion vectors using the full search method from the training images and then, train the codebook of the neural networks vector quantizer using these motion vectors. A motion vector can be estimated using the codebook as a motion prediction region. The codewords in the codebook represent the motion vectors for the input image sequences. Since the codebook is used as the search region for estimating the motion vectors, search points and computation can be reduced compared with the full search block matching algorithm. Additionally, the information required to transmit the motion vectors can be reduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.251-257
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• 2010

In this paper, we propose modified algorithm of motion vector detection for the pixel of image in the optical sensor. It is designed to reduce the amount of operation and have more accuracy in the motion detection than previous block matching algorithm. The proposed algorithm is implemented with Cyclone and fabricated using SEC 0.35um CMOS 1-poly-4-metal technology. The result of test with CARTESIAN ROBOT meets the desired performance.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.120-131
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• 1997

This paper prsents a new method that automatically recognizes the dimension lines (consisting of shape lines, tail lines and extension lines) from the mechanical drawings. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then the object lines and interpretation lines are vectorized by using several techniques such as thinning, line-vectorization, and vector-clustering. Finally, after recognizing arrowheads by using pattern matching, we recognize dimension lines from interpretation lines by using arrohead's directional vector and centroid. By using the methods of geometric modeling and mathematical operation, the proposed method readility recognizes the dimension lines from complex drawings. Experimental resuls are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.37-40
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• 2000

A fast method of Hangul address word verification is presented in this Paper. Pre-segmentation and recognition by DP matching is adopted in this paper. An address line image is over-segmented by analyzing the topology of connected components and the projection profile. A fast individual Hangul character verifier was developed by applying SVM (Support Vector Machine). The segmentation hypothesis was represented by lattice structure, and a best path search by dynamic programming generates the most probable segmentation path and the final verification score. The word verifier was tested on 310 address image DB, and it show the possibility of improvements of this method.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.275-280
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• 2004

In this paper, a very fast block matching scheme was proposed to reduce the computations of Block Sum Pyramid Algorithm for motion estimation in video coding. The proposed algorithm is based on Block Sum Pyramid Algorithm and Efficient Multi-level Successive Elimination Algorithm. The proposed algorithm can reduce the computations of motion estimation greatly with 100% motion estimation accuracy. The efficiency of the proposed algorithm was verified by experimental results.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.106-112
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• 2015

In this paper, we propose a method for correction of perspective distortion on a taken image. An image taken by a camera is caused perspective distortion depending on the direction of the camera when objects are projected onto the image. The proposed method in this paper is to obtain the normal vector of the plane through the depth information using a depth camera and calculate the direction of the camera based on this normal vector. Then the method corrects the perspective distortion to the view taken from the front side by performing a rotation transformation on the image according to the direction of the camera. Through the proposed method, it is possible to increase the processing speed than the conventional method such as correction of perspective distortion based on color information.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.185-193
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• 2009

Machine learning methods such as support vector machines and random forests yield nonparametric prediction functions of the form y = $f(x_1,{\ldots},x_p)$. As a sequel to the previous article (Huh and Lee, 2008) for visualizing nonparametric functions, I propose more sensible graphs for visualizing y = $f(x_1,{\ldots},x_p)$ herein which has two clear advantages over the previous simple graphs. New graphs will show a small number of prototype curves of $f(x_1,{\ldots},x_{j-1},x_j,x_{j+1}{\ldots},x_p)$, revealing statistically plausible portion over the interval of $x_j$ which changes with ($x_1,{\ldots},x_{j-1},x_{j+1},{\ldots},x_p$). To complement the visual display, matching importance measures for each of p predictor variables are produced. The proposed graphs and importance measures are validated in simulated settings and demonstrated for an environmental study.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.331-332
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• 2006

To enhance security and privacy in biometrics, changeable (or cancelable) biometrics have recently been introduced. The idea is to transform a biometric signal or feature into a new one for enrollment and matching. In this paper, we proposed changeable biometrics for face recognition using on PCA based approach. PCA coefficient vector extracted from an input face image. The vector is scrambled randomly and removed. When a transformed template is compromised, it is replaced by a new scrambling rule. In our experiment, we compared the performance between when PCA coefficient vectors are used for verification and when the transformed coefficient vectors are used for verification.