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New Calibration Method of Two-Dimensional Laser Scanner and Camera Based on LM-BP Neural Network

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSIP) 바로가기
  • 간행물
    International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
  • 통권
    Vol.9 No.7 (2016.07)바로가기
  • 페이지
    pp.231-244
  • 저자
    Jianlei Kong, Li Fan, Jinhao Liu, Lei Yan, Xiaokang Ding
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A281867

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원문정보

초록

영어
The calibration between a camera and a two-dimensional laser scanner (2DLS) is an essential step in the object detecting system. Many algorithms with linear model have been proposed. But these tend to solve intrinsic and extrinsic calibration parameters separately and are influenced seriously by the poor initial data, which leads to unstable and inaccurate results. Hence, a new nonlinear model based on the Back Propagation neural network trained by the Levenberg-Marquardt algorithm (LM-BP) is presented for calibration in this paper. Before the calibration, the original laser data is fitted linearly to avoid the ranging error and is optimized by an angular increment to reduce the step-angular error. Then, the calibration network with 4 inputs composed of the lasers points’ coordinates and constant 1, and 2 outputs are obtained, expected values of which are the coordinates of corresponding points in the image coordinates. The sum of square of errors between the network outputs and expected values is taken to adjust the modifications of the weights and thresholds with the Levenberg-Marquardt method to optimize the calibration model. Finally, compared with related researches, experimental results show that the accuracy of calibration between camera and 2DLS is significantly improved, and the detecting system is more suitable for actual measurement situations.

목차

Abstract
 1. Introduction
 2. Linear Model of the 2DLS-camera Calibration
 3. Calibration Model Based On LM-BP Neural Network
  3.1. Laser Data Improvement
  3.2. Design of LM-BP Neural Network
 4. Experiments
  4.1. Comparison
  4.2. Experiments with Real Data
 5. Conclusions
 Axknowledgements
 References

키워드

LM-BP neural network Nonlinear Calibration Model Two-dimensional Laser Camera

저자

  • Jianlei Kong [ Country College of Technology, Beijing Forestry University No. 35 East Qinghua Road, Haidian District, Beijing, China ]
  • Li Fan [ Country College of Technology, Beijing Forestry University No. 35 East Qinghua Road, Haidian District, Beijing, China ]
  • Jinhao Liu [ Country College of Technology, Beijing Forestry University No. 35 East Qinghua Road, Haidian District, Beijing, China ]
  • Lei Yan [ Country College of Technology, Beijing Forestry University No. 35 East Qinghua Road, Haidian District, Beijing, China ]
  • Xiaokang Ding [ Country College of Technology, Beijing Forestry University No. 35 East Qinghua Road, Haidian District, Beijing, China ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 간기
    격월간
  • pISSN
    2005-4254
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.7

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