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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

최근접 각도를 이용한 복수 레이저 영상 추적 방법 연구

A Study on the Multi-Laser Image Tracking Method using the Latest Approach Angle

한국사물인터넷학회논문지 / Journal of The Korea Internet of Things Society, (P)2466-0078;
2020, v.6 no.2, pp.37-43
https://doi.org/https://doi.org/10.20465/kiots.2020.6.2.037
조진표 (한밭대학교)
고호정 (한국폴리텍대학교)
김정호 (한밭대학교)
  • 다운로드 수
  • 조회수

초록

본 논문은 스크린과 레이저 발사장치의 이격거리 변화에도 복수 개의 레이저 영상을 안정적으로 인식할 수 있는최근접 각도 계산 방법을 제안하였다. 이 방법은 레이저 패턴 각도의 거리를 이용하여 사로를 인식하는 방법으로 레이저의 각도 추출은 레이블링 알고리즘을 이용하여 획득된 영상으로부터 레이저 영상을 검출하고, 허프 변환을 수행하여직선의 각도를 추출한다. 유사성 척도 중 유클리드 거리를 이용하여 추출한 레이저 영상의 각도와 기준 각도의 거리를계산하고, 계산된 거리 결과값을 이용하여 사로를 인식한다. 이격 거리를 “200cm∼400cm”로 변경하면서 실험한 결과, 모든 이격 거리에서 개별 사로를 100% 인식했다. 실험을 통해 제안한 방법의 신뢰성을 확인하였다.

keywords
IoT, MVS, Simulated shooting system, screen shooting system, laser image processing, 사물인터넷, 머신비전시스템, 모의사격 시스템, 스크린 사격 시스템, 레이저 영상 처리

Abstract

The paper proposed the method of calculating the latest approach angle that can reliably recognize multiple laser images even with the change in separation distance between screen and laser launch device. This method recognizes the angle of the laser pattern angle by using the distance of the laser pattern angle, and the angle extraction of the laser detects the laser image from the acquired image using the labeling algorithm, and performs the huff conversion to extract the angle of the straight line. The distance of the reference angle and angle of the laser image extracted using Euclidean distance among similarity scales is calculated, and the furnace is recognized using the calculated distance result value. Experiments with changing the separation distance to "200 cm to 400 cm" showed 100% recognition of individual strands at all separation distances. The experiment confirmed the reliability of the proposed method.

keywords
IoT, MVS, Simulated shooting system, screen shooting system, laser image processing, 사물인터넷, 머신비전시스템, 모의사격 시스템, 스크린 사격 시스템, 레이저 영상 처리

참고문헌

1.

K.T.Kim, “Development of improved door feed hanger clamping check systems using laser illumination pattern”, Master’s Thesis of Ulsan University, Korea, pp.1-5, 2012.

2.

Y.E.Kim, “User Interface Research of Computer Vision Industrial Inspection Software ”, Master’s Thesis of Yonsei University, Korea, pp.1-5, 2018.

3.

C.H.Cho, “Detecting shooting result of image processing based and Cloud base management system”, Doctor’s Thesis of Chonnam National University, Korea, pp.49-61, 2016.

4.

S.W.Namgung, “Study on the Single Target Shooting System using a Laser Beam”, Master’s Thesis of Kwangwoon University, Korea, pp.3-28, 2002.

5.

T.G.Lee, “Picking Out the Point of Impact for Shooting Simulation Using Image Processing”, Master’s Thesis of Chonnam National University, Korea, pp.11-28, 2009.

6.

J.H.Kim, “Image Fire Training System Using a Laser Beam and Method for Processing the Information of the Same”, KR Patent 10-1115873, Korea, 2012.

7.

S.J.Kang, J.H.Kim and S.W.Chung, “Development of Screen Shot System using Infrared Laser”, Journal of Korea Academia-Industrial cooperation Society, Vol.13, No.3, pp.1325-1329, 2012.

8.

H.C.Jeong and S.H.Jung, “Laser Pattern Based Simulated Shooting System and Its Implementation”, Journal of Korea Multimedia Society, Vol.21, No.10, pp.1171-1181, 2018.

9.

H.C.Jeong, “Simulated Firing System Based on Laser Pattern and Image Analysis”, Master’s Thesis of Chanwon National University, Korea, pp.16-40, 2018.

10.

Elan Dubrofsky, “Homography Estimation”, 2009.

11.

S.J.Young, “Image Interpolation Methods using Edges Detected from the Expanded Binary Image”, Master’s Thesis of Hanyang University, Korea, pp.8-36, 2009.

12.

T.W.Kim, “A vehicle license plate recognition system using morphological ROI(region of interest) map generated from morphology operation”, Master’s Thesis of Graduate School Korea Polytechnic University, Korea, pp.14-19, 2017.

13.

J.D.Park, C.H.Park, B.H.Park and H.K.Seong, “A Study on Labeling for License Plate Recognition”, Journal of Korean society of computer and information, Vol.22, No.1, pp.55-57, 2014.

14.

B.H.Cho and S.H.Jung, “Fast Hough Transform Using Multi-statistical Methods”, Journal of Korea Multimedia Society, Vol.19, No.10, pp.1747-1758, 2016.

15.

S.H.Kim, “A Technique of Calculating a Weighted Euclidean Distance with a Personalized Feature Set in Parametric Signature Verification”, Journal of the Korea Society for Simulation, Vol.14, No.3, pp.137-146, 2005.

한국사물인터넷학회논문지