반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

SIFT 특징점을 이용한 4채널 서라운드 시스템의 동적 영상 정합 알고리즘

Dynamic Stitching Algorithm for 4-channel Surround View System using SIFT Features

  • 국중진 (상명대학교 정보보안공학과) ;
  • 강대웅 (상명대학교 전자정보시스템공학과)
  • Joongjin Kook (Dept. of Information Security Engineering, Sangmyung University) ;
  • Daewoong Kang (Dept. of Electronic Information System Engineering, Sangmyung University)
  • 투고 : 2024.02.09
  • 심사 : 2024.03.20
  • 발행 : 2024.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, we propose a SIFT feature-based dynamic stitching algorithm for image calibration and correction of a 360-degree surround view system. The existing surround view system requires a lot of processing time and money because in the process of image calibration and correction. The traditional marker patterns are placed around the vehicle and correction is performed manually. Therefore, in this study, images captured with four fisheye cameras mounted on the surround view system were distorted and then matched with the same feature points in adjacent images through SIFT-based feature point extraction to enable image stitching without a fixed marker pattern.

키워드

과제정보

This research was funded by a 2023 research Grant from Sangmyung University.

참고문헌

  1. Jihye Jeon, Daehee Kim, Yoongi Yang, Joonki Paik, and Changsu Lee, "Image Distortion Compensation for Improved Gait Recognition," The Institute of Electronics Engineers of Korea - Signal Processing, vol. 46, no. 4, pp. 97-107, 2009.
  2. Vinh Ninh Dao and M. Sugimoto, "A Robust Recognition Technique for Dense Checkerboard Patterns." 2010 20th International Conference on Pattern Recognition, pp. 3081-3084, 2010.
  3. Jaehak Choi, Yonghwan Lee and Youngseop Kim, "Implementation of the Panoramic System Using Feature-Based Image Stitching", Journal of the Semiconductor & Display Technology, Vol. 16, No. 2. 2017.
  4. W. Sun, X. Yang, S. Xiao and W. Hu, "Robust checkerboard recognition for efficient nonplanar geometry registration in projector-camera systems," Proceedings of the 5th ACM/IEEE International Workshop on Projector camera systems, pp. 1-7. 2008.
  5. D. Hoiem, A. Efros and M. Hebert, "Automatic photo pop-up," ACM transactions on graphics, Vol. 24, No. 3, Jul, pp. 577-584. 2005. https://doi.org/10.1145/1073204.1073232
  6. M. Rufli, D. Scaramuzza and R. Siegwart, "Automatic detection of checkerboards on blurred and distorted images," IROS, pp. 3121-3126, 2008.
  7. M.W. Park, K.H. Jang and S.K. Jung, "Panoramic Vision System to Eliminate Driver's Blind Spots using a Laser Sensor and Cameras," Int. J. ITS Res, vol. 10, no. 3, Sep 1, pp. 101-114, 2010. https://doi.org/10.1007/s13177-012-0046-4
  8. T. Poggio and S. Edelman, "A network that learns to recognize three-dimensional objects," Nature (London), Vol. 343, No. 6255, pp. 263-266. 1990. https://doi.org/10.1038/343263a0