Dissertation > Excellent graduate degree dissertation topics show

Research and Implementation of Moving Obstacle Detection Technology Based on Monocular Vision

Author: DengZiJiu
Tutor: ZhangTie
School: Northeastern University
Course: Computational Mathematics
Keywords: monocular vision corner detection optical flow moving obstacle detection non-rigid body movement
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 76
Quote: 0
Read: Download Dissertation

Abstract


With the rapid economic growth and continuous promotion of the car, the number of the private car increases dramatically, as a result, the traffic accident which is caused by parking also occurs frequently. Therefore, advanced parking assistant system with anti-collision warning function attracts people’s extensively attention. As one of the most important techniques in parking assistant system, the detection of obstacles (particularly moving obstacles), which are at the back part of the vehicle, plays an active role in improving vehicle’s security performance and reducing traffic accidents, and may have a broad prospect.The research topic of the thesis is on-board monocular vision-based moving obstacles (which are at the back part of the vehicle) detection technology. It consists of three parts, in the first part, the existing corner detection algorithms are classified, two classic algorithms (Harris algorithm and SUSAN algorithm) are implemented and contrasted, which laid a solid foundation for the calculation of optical flow and image matching. The second part mainly focuses on the optical flow algorithms which are based on gradient and matching. A consistent data check technology is proposed, which makes the result of the optical flow more accuracy. The third part of the discussion focuses on moving obstacles detection under the circumstances of stationary vehicle and moving vehicle.In case of stationary vehicle, a based on three-image background recovery method is proposed; In case of moving vehicle, an optical flow-based algorithm is proposed and implemented, and the detection of non-rigid body movement is effective.Experiments show that the algorithm mentioned above could get a satisfactory result and is useful for moving obstacles detection and their movement characteristic classification.

Related Dissertations

  1. Research of Image Mosaic Technology,TP391.41
  2. Camera Calibration and Position and Pose Detecting on Vision Measurement System of PCB,TP391.41
  3. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  4. Research on Several Technologies of Image Analysis for the Objectification of Tongue Diagnosis,TP391.41
  5. Research and Implementation of Non-rigid Medical Image Registration Method Based on Improved Optical Flow Model,TP391.41
  6. The application of wavelet analysis in the feature extraction of palmprint,TP391.41
  7. Optical Flow Aided Navigation Inspired by Honeybee Vision,TP391.41
  8. Single Camera Calibration Method Based on Dual-mirror Imaging,TP391.41
  9. Mean-Shift -based KLT and target tracking study,TP391.41
  10. Target Tracking System Design and Implementation,TP391.41
  11. Infrared and visible image registration and fusion research,TP391.41
  12. Camera calibration Related Issues,TP391.41
  13. Coaxial different field picture image registration algorithm,TP391.41
  14. DM642-based infrared moving target detection and tracking technology,TP391.41
  15. PDE-based image registration and fusion method,TP391.41
  16. SURF feature based on monocular vision SLAM Research and Implementation,TP242
  17. Video scenes based on feature extraction classification technology research,TP391.41
  18. Based on Image Processing Method of automatic target,TP391.41
  19. Research on Fast Corner Extraction Algorithm in Camera Calibration,TP391.41
  20. Optical flow method based robot visual navigation,TP242
  21. Research on Key Technologies of Monocular Visual Odometry Based on DSP,TP391.41

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile