• Korean Journal of Geomatics
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• 제4권1호
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• pp.31-37
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• 2004

The aim of this research is comparing the existing approximation models (e.g. Affine Transformation and Direct Linear Transformation) with Rational Function Model as a substitute of rigorous sensor model of linear array scanner, especially push-broom sensor. To do so, this research investigates the mathematical model of each approximation method. This is followed by the assessments of accuracy of transformation from object space to image space by using simulated data generated by collinearity equations which incorporate or depict the physical aspects of linear array sensor.

• Journal of the Optical Society of Korea
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• 제5권3호
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• pp.90-92
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• 2001

Direct and inverse mathematical operators of stereo transformation (stereo operators) are studied in this paper. The stereo operators install a one-to-one correspondence between three dimensional coordinates of any point in space and the stereo coordinates which can be displayed on the screen under the given conditions, i.e. stereo vision base and the position of viewer. The stereo operators can be applied to the analyses of stereoscopic image distortions when the stereo vision base and the position of viewer are changed.

• Korean Journal of Mathematics
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• 제28권4호
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• pp.877-888
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• 2020

In this paper we discuss about the image of Gabor frame under a unitary operator and derive a sufficient condition under which a unitary operator from L²(ℝ) to 𝑙²(ℤ) maps Gabor frame in L²(ℝ) to a Gabor frame in 𝑙²(ℤ).

• 한국방사선학회논문지
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• 제2권3호
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• pp.5-9
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• 2008

전산화단층촬영(CT)에 있어서 생기는 artifact를 제거하기 위해서 영상재구성 과정에 다양한 필터를 사용하고 있다. 이러한 artifact는 영상재구성 과정에 사용되는 수학적 오차와, 투영이미지와 실제 해부학적 구조간의 오차, 혹은 데이터 획득과정에서의 오차 등으로 인해 필연적으로 생길 수 밖에 없다. 본 연구에서는 Hann필터를 사용하였을 때 CT 영상에서의 artifact 제거효과를 정량적으로 분석하였다. Cut-off 주파수가 0.1인 경우에서 0.2씩 증가시키며 0.9까지에 대한 다양한 cut-off 주파수의 Hann필터에 대한 artifact제거 효과에 대한 결과를 보였다. 재구성 영상에서의 artifact에 대한 정량적 분석을 위해서 white image에 대한 CT 영상의 Noise Power Spectrum을 비교하였다.

• Journal of Welding and Joining
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• 제21권2호
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• pp.102-110
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• 2003

A visual sensor consisted of polygonal mirror, laser, and CCD camera was proposed to measure the distance to the weld joint for recognizing the joint shape. To scan the laser beam of the sensor onto an object, 8-facet polygonal mirror was used as the rotating mirror. By locating the laser and the camera at axi-symmetrical positions around the mirror, the synchronized-scan condition could be satisfied even when the mirror was set to rotate through one direction continuously, which could remove the inertia effect of the conventional oscillating-mirror methods. The mathematical modelling of the proposed sensor with the optical triangulation method made it possible to derive the relation between the position of an image on the camera and the one of a laser light on the object. Through the geometrical simulation of the proposed sensor with the principal of reflection and virtual image, the optical path of a laser light could be predicted. The position and direction of the CCD camera were determined based on the Scheimpflug's condition to fit the focus of any image reflected from an object within the field of view. The results of modelling and simulation revealed that the proposed visual sensor could be used to recognize the weld joint and its vicinity located within the range of the field of view and the resolution. (Received February 19, 2003)

• 한국전자통신학회논문지
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• 제9권9호
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• pp.977-982
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• 2014

본 논문에서는 고화질 IP 카메라로부터 입력되는 영상으로부터 실시간으로 화염을 검출할 수 있는 시스템을 제안한다. 먼저 FFmpeg 라이브러리를 이용하여 비디오 파일을 오픈하는 것처럼 IP 카메라로부터 전송되는 RTSP 스트림을 직접 오픈한다. 두 번째는 입력영상으로부터 혼합 가우시안 모델을 이용하여 배경영상을 추출한다. 그 다음에는 입력 영상과 배경영상간의 차신호로부터 전경영상을 구한다. 분리된 전경영상은 수학적 모폴로지 연산을 거쳐 후보영역으로 간주한다. 후보영역의 색정보와 화염의 동적 특성을 분석하여 최종적으로 화염을 검출한다. 실험 결과를 통하여 제안하는 방법이 화염을 검출하는 데 효과적인 것을 보인다.

• Journal of Information Processing Systems
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• 제9권4호
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• pp.575-591
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• 2013

Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.

• 대한수학교육학회지:학교수학
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• 제18권2호
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• pp.425-440
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• 2016

본 연구는 초등학교 2학년 1학기 '여러 가지 도형' 단원을 학습한 학생들이 갖고 있는 삼각형에 관한 개념 이미지를 확인하고자 한 것이다. 그 결과 학생들은 삼각형과 세모에 대하여 서로 다른 개념 이미지를 갖고 있음을 알 수 있었다. 삼각형의 정의를 기계적으로 암송할 수 있지만, 변과 꼭짓점에 대한 심상이 적절하게 형성되어 있지 않음으로 인해 삼각형을 판별하지 못하는 경우도 있었다. 무엇보다 삼각형이라는 용어는 각의 관점의 용어이지만, 2학년 교과서에서는 각의 개념을 도입하지 않은 채 변의 관점에서 도입함으로 인해 학생들은 각을 변이나 면으로 혼동하는 경우도 있었다. 이러한 결과를 바탕으로 초등학교 수학과 교육과정과 교과서의 개선 방안을 제안하였다.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1168-1182
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• 2017

In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.

• ETRI Journal
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• 제43권4호
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.