Dissertation > Excellent graduate degree dissertation topics show

Research on Texture Image Segmentation Based on Phase Field Model

Author: ZhouJiaNan
Tutor: WangWanLiang
School: Zhejiang University of Technology
Course: Computer technology
Keywords: Texture image Phase field Image Segmentation Texture features
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 109
Quote: 0
Read: Download Dissertation

Abstract


Texture segmentation is an important research content in image processing and pattern recognition , has been a focus for researchers . It is based on the characteristics of the difference between the same texture the consistency characteristics or different texture , the texture image is divided into a number of meaningful areas . Texture image segmentation is an important branch of the digital image processing , is the basis for many image analysis and machine vision applications . However , on the one hand, due to the numerous types of natural textures , shapes and sizes , and the complicated structure , on the other hand also because of the lack of knowledge of the mechanism of human visual system perceive texture , texture segmentation has been a major problem in the field of image processing . So far , the texture image segmentation is still a do not get a good solution to a challenging issue . Texture image segmentation research , carried out a careful study and summarize the currently widely used in texture description method and texture segmentation method , and choose from based on the theory of variational perspective texture image segmentation problem , given the a good texture image segmentation method . The phase transition theory of phase -field model is introduced into the texture image segmentation modeling and classic phase field model is proposed to improve the texture image segmentation algorithm based on the phase -field model . By the phase separation of the different gray pixels in the texture image , the image is divided into a grayscale interconnecting region , and the edges of the image to be characterized by the dynamic interface between different phases of the model in order to achieve the texture image in the geometric patterns characterized in segmentation and extraction. The algorithm uses the finite element approximation and adaptive mesh adjustment model is solved numerically . Lagrangian finite element space discrete model , in order to improve the characterization capabilities of the finite element mesh unit pattern content the grid optimization strategy adaptive adjustment of grid cells , thereby improving the grid cell pattern characterization effect. Synthetic image and jacquard fabric texture image segmentation experimental results show the effectiveness of the proposed algorithm .

Related Dissertations

  1. Research on Image Recognition Algorithm in the Forest Fire Prevention System,TP391.41
  2. Application Research of Digital Image Processing on Container Inspection,TP274.4
  3. Study on the Design and Biomechanical Behaviors of Individualized Artificial Knee Joint,R318.1
  4. Research on the Watermark Method Based on HVME and Contourlet,TP309.7
  5. The Depth Estimation Based on Monocular Night Vision Image,TP391.41
  6. Unmanned intelligent vehicle based on monocular vision -based road detection,TP391.41
  7. Research of Digital Image Segmentation,TP391.41
  8. Research of Infrared Image Segmentation for Power Equipment in Substation,TP391.41
  9. The Research of Image Segmentation Based on Fractal and Active Contour Model,TP391.41
  10. The Pattern Recognition Design of Bus Passenger Count System,U491.17
  11. The Preliminary Research on Computer-aided Detection of Lung Nodule Based on CT Images,TP391.41
  12. The Reasearch on License Plate Location Based on Regional Synthetic Characteristic and Its Application,TP391.41
  13. Research on Medical Image Retrieval Based on Texture and Shape,TP391.41
  14. Research into Chinese Envelope Image Segmentation and Destination Address Block Location,TP391.41
  15. Based on Differential Evolution Algorithm GVF Snake Model for PET Medical Image Processing,TP391.41
  16. A Technology of Image Segmentation Based on Cloud Theory,TP391.41
  17. Research and Design of Navigation Algorithm for Vision-based Mobile Robot,TP242.62
  18. Anti-bounce Bidirectional K-level Tolerant Steel-bar Counting System Research,TP274
  19. Color-based target tracking mobile robot vision system,TP242.6
  20. CAAC Aircraft Registered Number Recognition,F562
  21. Phase-field Modeling of Liquid/Solid Phase Transformation of Al-Si Alloy during Near-Liquidus Casting,TG292

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