무한다중상 형성 원리 이해를 위한 지오지브라 활용 융합 교육 자료 개발: S 영재학교 재학생을 대상으로

최경식 학습자중심교과교육학회 2023 학습자중심교과교육연구 Vol.23 No.17

Objectives In this study, it was analyzed the understanding of the principle of formation of infinite multiple image of first-year students in a gifted school, and developed convergence education materials for the students' level of understanding. Methods A questionnaire was developed in consideration of the formation of infinite multiple images, the way two mirror images appear in infinite multiple images, and the recognition of the formation of infinite multiple images according to situational changes. Afterwards, 16 first-year students in S gifted school in Korea were asked to respond to the questionnaire, and the results were analyzed. Results Analyzing the students' understanding of infinite multiple image formation, most of the students were aware of infinite multiple image, but they did not know exactly how the infinite multiple image was formed. Based on the results, convergence educational materials based on ray diagram for the infinite multiple image formation were developed using GeoGebra math software. Conclusions The convergence education materials developed in this study can be used for gifted school students' understanding of infinite multiple images, and can be used later for convergence classes for general school students.

교차배열 변환기를 이용한 복합 위상배열 초음파 영상화 기법: 영상화 알고리즘 및 이중 선형 영상

박춘수 한국비파괴검사학회 2019 한국비파괴검사학회지 Vol.39 No.1

Ultrasonic phased array imaging has been primarily developed to visualize defects inside structures. The phased array images are used as results of phased array ultrasound testing(PAUT). Conventional PAUT generally needs an array transducer that has a single resonant frequency. Nowadays, many kinds of materials are used as various structural components, and they need appropriate frequencies for PAUT depending on each material. In addition, nonlinear PAUT has been newly proposed to see defects hidden from linear PAUT. These recent trends led us to develop multiple phased array ultrasonic imaging. The multiple phased array imaging needs an inter-leaved array transducer composed of two different resonant frequencies. An element of a resonant frequency is placed between another element of the other frequency. The multiple phased array imaging can provide two linear images and two nonlinear images by using each transmitting-receiving combination. Two linear phased array images are obtained by each resonant frequency, and two nonlinear phased array images are made up of higher-harmonic image and sub-harmonic image. A multiple phased array imaging scheme is introduced, and the imaging algorithm is explained especially for linear imaging. Computer simulations confirm that the proposed method successfully shows two linear phased array images compatible with the conventional total focusing method images. Finally, experiments with a reference block clearly demonstrated that the proposed method and the inter-leaved array transducer fabricated work well for dual linear phased array imaging. 초음파 위상배열 영상은 재료 내부의 결함 상태를 영상으로 보여주는 비파괴검사 기법 중 하나이다. 기존의 위상배열 영상화 기법은 하나의 공진 주파수를 가지는 배열 변환기를 이용하여 영상을 얻는다. 본 논문에서 사용하는 교차배열 변환기는 2개의 공진주파수를 가지는 압전소자를 교차로 배열한 하나의 배열 변환기를 사용하여 신호를 송/수신한다. 이는 검사하고자 하는 재료의 특성에 따라 다양한 주파수가 요구되는 상황에서, 기존의 단일 주파수 배열 변환기 보다 다양한 상황에 대응이 가능한 장점이 있다. 이에 더해 선형 위상배열 영상으로는 관찰할 수 없는 결함 관찰이 가능한 비선형 영상화 기법에도 적용할 수 있다. 본 논문에서 제안하는 복합 위상배열 초음파 영상화 기법은 교차배열 변환기를 통해 획득된 신호를 이용하여 두 개의 선형 위상배열 영상과 두 개의 비선형 위상배열 영상을 구현할 수 있다. 선형 위상배열 영상은 각각의 공진 주파수 소자를 이용하여 얻을 수 있으며, 비선형 위상배열 영상은 비선형 고조파 영상과 비선형 저조파 영상을 구현할 수 있다. 본 논문에서는 복합위상배열 초음파 영상화에 대한 개념과 영상화 알고리즘에 대해 소개하고, 전산모사 실험을 통해 선형 영상화 알고리즘을 검증한다. 그리고, 제작된 교차배열 변환기를 이용하여 이중(dual) 선형 위상배열 영상 획득 결과를 관찰하였다.

저화질 영상 인식을 위한 화질 저하 모델 기반 다중 인식기 결합

김인중,류상진 한국정보처리학회 2010 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.17 No.3

In this paper, we propose a multiple classifier combination method based on image degradation modeling to improve recognition performance on low-quality images. Using an image degradation model, it generates a set of classifiers each of which is specialized for a specific image quality. In recognition, it combines the results of the recognizers by weighted averaging to decide the final result. At this time, the weight of each recognizer is dynamically decided from the estimated quality of the input image. It assigns large weight to the recognizer specialized to the estimated quality of the input image, but small weight to other recognizers. As the result, it can effectively adapt to image quality variation. Moreover, being a multiple-classifier system, it shows more reliable performance then the single-classifier system on low-quality images. In the experiment, the proposed multiple-classifier combination method achieved higher recognition rate than multiple-classifier combination systems not considering the image quality or single classifier systems considering the image quality. 본 논문에서는 화질 저하 모델에 기반한 다중 인식기 결합을 이용하여 저화질 영상에 대한 인식 성능을 개선하기 위한 방법을 제안한다. 제안하는 방법은 화질 저하 모델을 이용해 특정 화질에 각각 특화된 복수의 인식기들을 생성한다. 인식 과정에서는 인식기들의 결과를 가중 평균에 의해 결합함으로써 최종 결과를 결정한다. 이 때, 각 인식기의 가중치는 입력 영상의 화질 추정 결과에 따라 동적으로 결정된다. 입력 영상의 화질에 특화된 인식기에는 큰 가중치를, 그렇지 않은 인식기에는 작은 가중치를 지정한다. 그 결과, 입력 영상의 화질 변이에 효과적으로 적응할 수 있다. 뿐만 아니라, 복수의 인식기를 사용하기 때문에 저화질 영상에 대하여 단일 인식 시스템보다 더욱 안정적인 성능을 나타낸다. 제안하는 다중 인식기 결합 방법은 화질을 고려하지 않은 다중 인식기 결합 방법이나, 화질을 고려한 단일 인식 방법과 비교하여 더 높은 인식률을 보였다.

3차원 Multiple-Input Multiple-Output 간섭계 ISAR 영상형성기법

강병수(Byung-Soo Kang),배지훈(Ji-Hoon Bae),양은정(Eun-Jung Yang),김경태(Kyung-Tae Kim) 한국전자파학회 2015 한국전자파학회논문지 Vol.26 No.6

본 논문에서는 다중입력-다중출력(multiple-input, multiple-output: MIMO) 간섭계(interferometric) 레이다 네트워크 시스템을 기반한 MIMO 간섭계 역합성 개구면 레이다(inverse synthetic aparture radar: InISAR) 영상 형성기법에 관해 연구하였다. MIMO 간섭계 레이다 네트워크 시스템 내에서는 여러 바이스태틱 InISAR 영상들이 형성되며, 이들을 인코히리언트(incoherent)하게 합성함으로써 MIMO InISAR 영상을 형성할 수 있다. 여기서, 바이스태틱 InISAR 영상은 바이스태틱 기하구조 내에서의 표적에 대한 산란분포를 3차원의 형태로 도시한다. 상기 MIMO InISAR 영상에서는 다중 각도에서의 바이스태틱 산란 현상을 3차원의 형태로 도시하기 때문에, 표적의 다양한 산란 정보를 제공함과 더불어, 표적 식별 시유용한 특징 벡터(feature vector)로써 활용될 수 있다. 시뮬레이션을 통해, 제안된 MIMO InISAR 영상 형성 기법을 이용함으로써 표적에 대한 다중각도에서의 바이스태틱 산란분포가 3차원의 형태로 도시되는 것을 확인할 수 있다. In this paper, we propose a multiple-input, multiple-output(MIMO) interferometric radar network system to generate three-dimensional (3-D) MIMO interferometric inverse synthetic aperture radar(InISAR) image. In the MIMO interferometric radar network system, the MIMO InISAR image can be formed by an incoherent summation of multiple bistatic InISAR images that show 3-D scatterers of a target observed at different bistatic interfermetric configurations, respectively. Because bistatic-sccattering physics of a target at different viewpoints are visible in the 3-D MIMO InISAR image, it can provide various scatterering physics properties of a target, and can be used for target classification as a useful feature vector. Simulations validate that our proposed method successfully finds locations of scatterers of a target in MIMO radar interferometric network system.

Generalized MAP Estimation Via Parameter Scheduling and Maximizer of the Posterior Marginal Estimate for Image Reconstruction Using Multiple Halftone Images

Yohei Saika,Kenta Morimoto 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10

We studied performance of a generalized MAP estimation which was regarded as the maximizer of the posterior marginal (MPM) estimate for image reconstruction via multiple halftone images for a set of grayscale images generated by an assumed true prior and a 256-grayscale standard image. By making use of numerical simulations for those images, we clarified that performance of the generalized MAP estimation is improved with the increase in the number of the halftone images for image reconstruction, if we tune parameter scheduling appropriately. Also, we found that the present method reconstructs original images more accurately than the conventional MAP estimation and the MPM estimate.

탄성파를 적용한 다중 위상 MR Elastography로부터의 점탄성 정수의 측정

정남채,Jung, Nam-Chae 한국융합신호처리학회 2012 융합신호처리학회 논문지 (JISPS) Vol.13 No.3

의료분야에서 조직의 경화는 진단 또는 질환의 진행상황의 파악에 이용되는 중요한 정보의 한 가지이며, 객관적인 진단을 위해서는 경화의 정량적 계측법이 중요하다. 경화의 지표인 점탄성 정수를 비침습적으로 계측하는 방법으로 MRE(Magnetic Resonance Elastography) 법이 제안되고 있다. MRE 법에서는 전파파(propagating wave)의 국소 파장과 국소 감쇠율로부터 점탄성 정수를 구하는데 MRE 화상은 S/N 비가 낮아지므로, 잡음의 영향을 감소시키기 위하여 다중 위상 MRE 화상을 이용한 방법이 검토되고 있다. 본 연구에서는 다중 위상 MRE 화상에 함수를 적용하여 점탄성 정수를 측정하는 방법을 제안한다. 제안 방법은 다중 위상 MRE 화상에 점탄성파를 적용시키지만, 점탄성 정수의 공간방향으로의 변화율이나 화상에 포함된 잡음에 따라 측정값의 공간분해능을 임의적으로 설정할 수 있다는 장점이 있다. 시뮬레이션 화상을 이용한 실험과 silicone-gel phantom을 이용한 실험에 의하여 제안된 방법의 유효성을 확인하였다. In the medical field, the hardening of tissues is one of important informations used in diagnosis or understanding progress of disease, a quantitative measuring method of hardening is important for objective diagnosis. It has been proposed MRE(Magnetic Resonance Elastography) method that measures an index of hardening, viscoelastic properties in a noninvasive. Because the S/N ratio of MRE images go down when measuring viscoelastic properties from local wavelength and local damping factor of a propagating wave in MRE method, methods using multiple phase MRE images have been examined to decrease the effect of noise. We propose a method measuring viscoelastic properties after Fitting a function for multiple phase MRE images in this research. This proposed method has a advantage to set up arbitrarily the variation rate of a space direction of viscoelastic properties or the spatial resolution of measuring values according to changing of the noise included in images, though it applies viscoelastic wave for multiple phase MRE images. We confirmed the effectiveness of a proposed method by experiment using simulation images and experiment using silicone-gel phantom.

3D Integral Imaging Display using Axially Recorded Multiple Images

조명진,신동학 한국광학회 2013 Current Optics and Photonics Vol.17 No.5

In this paper, we propose a 3D display method combining a pickup process using axially recorded multiple images and an integral imaging display process. First, we extract the color and depth information of 3D objects for displaying 3D images from axially recorded multiple 2D images. Next, using the extracted depth map and color images, elemental images are computationally synthesized based on a ray mapping model between 3D space and an elemental image plane. Finally, we display 3D images optically by an integral imaging system with a lenslet array. To show the usefulness of the proposed system, we carry out optical experiments for 3D objects and present the experimental results.

Double Random Phase Encryption using Orthogonal Encoding for Multiple-Image Transmission

이인호,조명진 한국광학회 2014 Current Optics and Photonics Vol.18 No.3

In this paper we extend double random phase encryption (DRPE) using orthogonal encoding from single-image transmission to multiple-image transmission. The orthogonal encoding for multiple images employs a larger Hadamard matrix than that for a single image, which can improve security. We provide a scheme for DRPE with an orthogonal codec, and a method for orthogonal encoding/decoding for multiple-image transmission. Finally, simulation results verify that the DRPE using orthogonal encoding for multiple images is more secure than both the conventional DRPE and the DRPE using orthogonal encoding for a single image.

목표물 검출 및 인식을 위한 잡음 형태에 따른 다중 모델 가이디드 영상 필터

김선영,강창호,조준후,송진우,박찬국 제어·로봇·시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.8

In this paper, a MMGIF (Multiple Model Guided Image Filter) is proposed to eliminate the additive noise in a measured image and to eventually detect and recognize targets in the vision-used system reliably. We only consider Gaussian noise and salt-and-pepper noise (impulse noise), which are practical and representative noise types in images. Therefore, the proposed MMGIF consists of two different GIFs (Guided Image Filters) and applies the appropriate GIF according to the noise type. One GIF model is a standard GIF for removing white Gaussian noise, and the other model is a Laplacian GIF for salt-and-pepper noise, which generally occurs in CCD camera images. Furthermore, in order to select the proper model, an image noise identification method is also proposed in this paper. The proposed algorithm estimates the image noise type based on a logistic regression algorithm by using kurtosis, skewness, and normality obtained from the estimated noise distribution. The performance of the proposed algorithm is evaluated in terms of peak signal-to-noise ratio and image enhancement factor through several simulations. .

Multiple butterfly recognition based on deep residual learning and image analysis

Xi Tianyu,Wang Jiangning,Han Yan,Lin Congtian,Ji Liqiang 한국곤충학회 2022 Entomological Research Vol.52 No.1

Insect recognition is crucial for taxonomy. It helps researchers to process tremendous and various ecology data. Most studies focus on fine-tuning the deep learning network or altering the algorithm to enhance the identification accuracy, and some useful tools have been generated with these methods. This study focuses on the influence of image data on the recognition model. The single data set source of the existing automated identification tools is relatively simple, and the competition-based data set released only focuses on evaluating the model at present. For the first time, this article integrates butterfly image data sets from multiple sources, covered illustrated books, and popular butterfly science websites. The image types include standard specimen images, illustrated book scan images and camera shots. In addition, these images included not only fixed poses, but also various other images of butterflies in natural poses. The size of these images is also various. The testing data set is new data that does not belong to the training set, which also verifies the generalizability of the model, indicating that in practical applications this model can identify new images. This testing method is a breakthrough compared to the previous work. We designed different data sets using the ResNet18 network to train a classifier, which achieves a validation accuracy of 86% in the end of the analysis. By adjusting the data sets, the accuracy changes as well. This study provides a method to recognize hundreds of butterfly species and analyzes the testing progress from the point of view of data. It is the first to combine butterflies from multiple countries in a single data set, with a recognition accuracy that outperforms previous experiments, to the best of our knowledge. We further analyze the testing results of butterfly recognition at the family and genus level. We perform two more experiments to demonstrate the model in the case of similar species or genus.