Dissertation > Excellent graduate degree dissertation topics show

Based on high resolution satellite images of traffic flow parameters Extraction

Author: SunZuo
Tutor: LiangYanPing
School: Beijing Jiaotong University
Course: Transportation Planning and Management
Keywords: High-resolution satellite imagery Object-oriented image analysis Support vector machine classification Feature space Traffic flow parameter extraction
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 232
Quote: 5
Read: Download Dissertation

Abstract


Existing traffic sensors collect traffic information there are many limitations , along with high-resolution satellite images commercialization emerges from a wide range of remote sensing images for road traffic information , has become the intelligent transportation system information collection technology , a research hotspot. This paper aims to study from high-resolution satellite images in the detection of vehicles, and further extracting traffic flow parameters. The study includes the following aspects: ( 1 ) characteristics for high resolution remote sensing images , drawing on visual interpretation of the principles of object-oriented classification of vehicles taken detection method . By multiscale segmentation and target feature extraction, creating an image object feature space to achieve the vehicle identification and classification ; ( 2 ) based on support vector machine classification method of detecting a vehicle . According to the characteristics of the vehicle in the image , the image texture feature extraction , image texture features obtained , from which the selected sample of vehicles and non- vehicle samples , training the classifier , set the kernel function parameters, image classification , enabling the vehicle to detect ; ( 3 ) results of data analysis for vehicle detection for traffic flow parameter extraction , including direct and indirect traffic flow parameters extracted traffic flow parameter extraction ; ( 4 ) QuickBird2 experimental data using two detection method is validated , the results show that the object-oriented image classification more accurate vehicle detection method , and the overall accuracy of the error matrix theory, more than 90% . And further select the two sets of data , the method comparison test , analyze the factors that affect the detection performance , including roads lined with trees and buildings is caused by dark shadows the main vehicle detection error . In this study, for intelligent transportation systems rich in information collection technology , traffic flow parameter extraction means expansion is important.

Related Dissertations

  1. Yeyahu typical wetland plant information extraction based on the analysis of spectral characteristics,P237
  2. Sports Metadata Extraction Technology Research and Implementation Based on Video Content,TP391.41
  3. Studies of Some Key Techniques in Hyperspectral Classification,P237
  4. Research on Video Based Face Tracking and Recognition,TP391.41
  5. Research on Face Recognition Approach Using Subspace with Embedding Neighborhood Discrimimant Relation,TP391.4
  6. The matrix perturbation a number of issues research,O151.21
  7. Application of Water-flooded Zone Identifying Based on Computational Learning,TP391.4
  8. Research on Technology of Human Face Detecting and Tracking,TP391.41
  9. Study of Water Quality Assessment and Parameter Prediction Based on Support Vector Machine,X824
  10. Compression encoding of the video image of the human face,TP391.41
  11. Applications of SVM to Predict Silicon Content in Hot Metal,TF54
  12. An Eigenspace Based Approach for 3D Object Recognition,TP391.41
  13. Projection on Speech Features Space Improves the Performance of Speaker Identification,TP391.42
  14. Medical Image Classification Based on SVM,TP391.41
  15. Study and Related Implementation of Robust Algorithm for Adaptive Beam-forming,TN911.7
  16. Continuous Audio Stream Segmentation and Classification Systems Research,TP18
  17. Method of Monitoring Vegetation Information on the Mining Based on Multiple Remote Sensing Data,P237
  18. Chinese Personal Name Disambiguation in Web People Search,TP391.1
  19. Multi-class Classification Algorithm Research Based on Fuzzy Support Vector Machines,TP181
  20. Support Vector Regression and Its Application,F224

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