Dissertation > Excellent graduate degree dissertation topics show

Research of Movin Obiect Detection and DSP Implemention

Author: MengJieCheng
Tutor: LvHong
School: Anhui University of Engineering
Course: Detection Technology and Automation
Keywords: moving object detection pre-processing of image morphological the three frame difference the of model mixture Gaussianbackground DM642
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 31
Quote: 0
Read: Download Dissertation

Abstract


Moving object detection is an important topic in the field of the research on computer vision. Moving target detection is designed based on analyzing the sequences of video or image and segmented the moving target which would be interesting from the background, obtaining the target area and its related parameters, which is the basis of target tracking, behavior recognition,scene understanding and other high-level visual processing. Moving object detection is widely used in all areas, such as the video surveillance system, the interaction of human-computer, the compression of image, intelligent transportation systems, industrial control, biomedicine, weather analysis, weapons and equipment. So The moving object detection is not only very important on the research value and practical significance, but also for other field of computer vision research,which will promot an important postion.The paper which has thoroughly studied the video image sequence in the moving target detection method with the camera fixed case uptake in the video image sequence as the research object. Firstly, this paper explain the general steps of some commonly used methods of moving target detection including the optical flow method, frame difference method, the background difference method, and also which analysis of the principles of these methods and processes, and compares their advantages and disadvantages. Then I studied the view of the background difference method of common background model, and the analysis and comparison of different background modeling algorithms. At last I research the image pretreatment, morphological processing in depthly.This paper studies the method of moving target detection on based on mixture of Gauss background model. It is the key of this paper. This article first introduces the method for moving target detection on the traditional of mixed Gauss background model, and then pointed out that the traditional hybrid Gauss background model of moving target detection method in the presence of the large amount of calculation, error detection and" slur" problem. So the article proposed one new method for moving target detection based on combining the three frame difference method and mixed Gauss background model. The improved algorithm using adaptive median filtering method on the input image pretreatment, throughing the three frame difference with area method to judge whether the existence of moving targets in video image, if there exists a moving object for the next processing, finally we can use the mathematical morphology processing. Experiments shows that the method can overcome these shortcomings of the traditional algorithm based on mixture Gaussian background model, can effectively detect the moving target.Finally, the paper introduces the hardware platform which the chip DM642is the central processor of by TI company. Introduce the module circuit of the system, including the video capture module, the video display module, and extended memory module. Design the system software process, and part of the porting and optimization of the algorithm.

Related Dissertations

  1. Research on Form Characteristics and Conserved Countermeasures of Historical Conserved Area of Changchun City,TU984.114
  2. FPGA/DSP Image Co-processor Technology and Ethernet Data Transmission,TP391.41
  3. Parent Culture and Early Individual Development of Perinereis Aibuhitensis under the Cultivation Condition with Gracilaria Tenuistipitata,S968.9
  4. Effects of Low Temperature Stress on Blood Physiological and Biochemical Indexes of Oreochromis Hornorum,S917.4
  5. Establishment of the Molecular Identifying System of Curvualria and Application in Difficult Species,Q949.32
  6. The Identificationand Rapdanalysis of Wheat Root Lesion Pathogens in Henan Province,S435.121
  7. The Morphological Structural Model and Visualization of Rapeseed (Brassica Napus L.) Plant,S565.4
  8. Peach fruit moth and fungi pathogenic role of extracellular enzymes,S476.1
  9. Research on Noise Tolerance of Morphological Associative Memory Networks,TN911.4
  10. The Research and Application of H.264 Coding Technology in the Video Monitoring System,TP277
  11. Research & Implementation of Moving Object Detection Based on Fish-eye Camera,TP391.41
  12. The Research and Implementation of Background Modeling and Updating Algorithm Based on Mixture Gaussian Model,TP391.41
  13. Study on Automatic Scaling of the F Layer Traces in Ionogram,TP391.41
  14. Study on the Detection of Lung Nodules from CT Images Based on Hessian Matrix,TP391.41
  15. Fundus Image Segmentation Based on SVM and Template Matching,TP391.41
  16. Research and Implementation of Embedded Network Video Detection Techniques,TP391.41
  17. Moving Object Detection and Tracking in Dynamic Scene,TP391.41
  18. Research on Moving Object Detection Schemes Based on the Bayesian Theory,TP391.41
  19. The Study of the Background Modeling Algorithm for Object Detection and Implementation Based on DSP Technique,TP391.41
  20. Transport System-based Video Motion Detection,TP391.41
  21. Reasearch on Automatic Acquisition and Recognition System of Train Carriage License Image,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