• 음성과학
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• 제11권2호
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• pp.211-216
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• 2004

In this paper, we present a fast encoding algorithm for vector quantization with an approximate Euclidean distance calculation. An approximation is performed by converting floating point to the near integer. An inequality between the approximate Euclidean distance and the nearest distance is developed to avoid unnecessary distance calculations. Since the proposed algorithm rejects those codewords that are impossible to be the nearest codeword, it produces the same output as conventional full search algorithm.

• International Journal of CAD/CAM
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• 제8권1호
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• pp.45-53
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• 2009

As the point sampling technology evolves rapidly, there has been increasing need in generating tool path from dense point set without creating intermediate models such as triangular meshes or surfaces. In this paper, we present a new tool path generation method from point set using Euclidean distance fields based on Algebraic Point Set Surfaces (APSS). Once an Euclidean distance field from the target shape is obtained, it is fairly easy to generate tool paths. In order to compute the distance from a point in the 3D space to the point set, we locally fit an algebraic sphere using moving least square method (MLS) for accurate and simple calculation. This process is repeated until it converges. The main advantages of our approach are : (1) tool paths are computed directly from point set without making triangular mesh or surfaces and their offsets, and (2) we do not have to worry about no local interference at concave region compared to the other methods using triangular mesh or surface model. Experimental results show that our approach can generate accurate enough tool paths from a point set in a robust manner and efficiently.

• International Journal of Contents
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• 제11권2호
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• pp.9-14
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• 2015

We propose a new distance measure between 2-dimensional points to provide a total order for an entire point set and to reflect the correct geometric meaning of the naturalness of the point ordering. In general, there is no total order for 2-dimensional point sets, so curve reconstruction algorithms do not solve the self-intersection problem because the distance used in the previous methods is the Euclidean distance. A natural distance based on Brownian motion was previously proposed to solve the self-intersection problem. However, the distance reflects the wrong geometric meaning of the naturalness. In this paper, we correct the disadvantage of the natural distance by introducing a polar-natural distance, and we also propose a new curve reconstruction algorithm that is based on the polar-natural distance. Our experiments show that the new distance adequately reflects the correct geometric meaning, so non-simple curve reconstruction can be solved.

• 한국산업정보학회논문지
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• 제19권4호
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• pp.53-63
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• 2014

이동 컴퓨팅 환경에서 사용자 움직임 판별은 해결해야 할 중요한 이슈중의 하나이다. 본 논문에서는 유클리디안 거리 유사도를 이용하여 스마트폰 사용자의 움직임을 인식하고 판별하기 위한 방법을 제시한다. 제안된 방법에서는 GPS와 가속 센서를 이용하여 데이터를 수집하고, 수집된 데이터를 이용하여, 사용자의 정지, 걷기, 뛰기, 차량이동을 판별한다. 제안된 방법의 타당성과 효율성을 검증하기 위하여, 안드로이드 시스템에 유클리디안 거리 유사도의 여러 변형을 이용한 응용프로그램을 구현하여 그 정확도를 측정하였다. 실험 결과, 사용자 움직임 종류를 90% 이상의 정확도를 가지고 판별해 내었다.

• East Asian mathematical journal
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• 제17권2호
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• pp.303-308
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• 2001

Let K($z,\gamma$) denote the euclidean curvature of the curve $\gamma$ at the point z. Flinn and Osgood proved that if f is a univalent mapping of the open unit disk D={z:|z|<1} into itself with f(0)=0 and |f'(0)|<1, then $K(0,\gamma){\leq}K(0,f\;o\;\gamma)$ for any $C^2$ curve $\gamma$ on D through the origin with $K(0,\gamma){\geq}4$. In this paper we establish a generalization of the Flinn-Osgood Monotonicity Theorem.

• Journal of applied mathematics & informatics
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• 제42권2호
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• pp.433-444
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• 2024

Our study explores the connection between the Pythagorean theorem and the Fixed-point theorem in metric spaces. Both of which center around the concepts of distance transformations and point relationships. The Pythagorean theorem deals with right triangles in Euclidean space, emphasizing distances between points. In contrast, fixed-point theorems pertain to the points that remain unchanged under specific transformations thereby preserving distances. The article delves into the intrinsic correlation between these concepts and presents a novel study in Euclidean metric spaces, examining the relationship between contraction mapping and Pythagorean Right Triangles. Practical applications are also discussed particularly in the context of image compression. Here, the integration of the Pythagorean right triangle paradigm with contraction mappings results in efficient data representation and the preservation of visual data relation-ships. This illustrates the practical utility of seemingly abstract theories in addressing real-world challenges.

• Journal of Biosystems Engineering
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• 제22권2호
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• 한국콘텐츠학회논문지
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• 제19권1호
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• pp.125-131
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• 2019

소실점이란 실제 공간의 평행한 선들이 영상 내에 투영되면서 한곳에 모이는 점으로, 도로 공간에서의 소실점은 매우 중요한 공간정보이다. 도로 공간에서의 소실점을 이용해 추출된 차선의 위치를 개선하거나, 깊이지도 영상을 생성할 수 있다. 본 논문에서는 자동차의 시점을 기준으로 도로를 촬영한 영상을 Deep Neural Network(DNN)과 Histogram of Oriented Gradient(HoG) Feature를 이용한 소실점 검출 방법을 제안한다. 제안하는 알고리즘에서는 영상을 블록별로 나눠서 주요 에지 방향을 추출하는 HoG Feature 추출 단계와 DNN 학습 단계, 그리고 Test 단계로 나뉜다. 학습단계에서는 자동차 시점으로 기준으로 도로 영상 2300장으로 학습을 진행한다. 그리고 Test 단계에서는 Normalized Euclidean Distance(NormDist) 방법을 사용하여 제안하는 알고리즘의 효율성을 측정한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.901-904
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• 2000

A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then fingerprint is divided into non-overlapping blocks with respect to the core point and features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.

• 한국시뮬레이션학회논문지
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• 제7권1호
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• pp.27-37
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• 1998

Simulation output is generally stochastic and autocorrelated, and includes the initial condition bias. To exclude the bias, the determination of truncation point has been one of important issues for the steady-state simulation output analysis. In this paper, two methods are presented for detection of truncation point in order to estimate efficiently the steady-state measure of simulation output. They are based on the Euclidean distance equation, and the backpropagation algorithm in Neural Networks. The experimental results obtained by M/M/1 and M/M/2 show that the proposed methods are very promising with respect to coverage and relative bias. The methods could be used for the on-line analysis of simulation outputs.