Dissertation > Excellent graduate degree dissertation topics show

Algorithmic Research for Automatic Image Annotation Based on Color Constancy and Multiple Instance Learning

Author: ChengYouZhong
Tutor: XuDe
School: Beijing Jiaotong University
Course: Computer Science and Technology
Keywords: Image annotation Image sub_blocking Color constancy Multiple instance learning Support vector machines
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 182
Quote: 1
Read: Download Dissertation

Abstract


Automatic image annotation has been an active research topic in recent years due to its potentially fundamental impact on image understandings and that manual image annotation for indexing and then later retrieving image collections is an expensive and labor intensive procedure.In this paper, a novel automatic image annotation algorithm is proposed, which extends color constancy and Multiple Instance Learning (MIL), and their applications to the problem of block-based image annotation. Images are viewed as bags, each of which contains a number of instances corresponding to blocks obtained from image sub_blocking. To correct images using an appropriate color constancy method can make low-level features more robust. Then we can apply MIL technique to get more proper instance prototypes to construct bag features which represent corresponding categories. The thesis first introduces some classical color constancy algorithms and applies general Gray-World algorithm to preprocess images, which is based on grey-world hypothesis. A new image sub_blocking scheme is proposed, which can improve the efficiency. Then the bag features are obtained by applying MIL technique on the image blocks, where the enhanced DD algorithm and a faster searching algorithm are applied to improve the efficiency and accuracy. Finally, the bag features are input to a set of SVMs for finding the optimum hyperplanes for automatically annotate images.Our proposed annotation approach demonstrates a promising performance for an image database of 2000 general-purpose images from COREL, as compared with some current peer algorithms in the literature.

Related Dissertations

  1. Research and Optimized Realization of Self-validating Sensor Fault Diagnosis Algorithm Based on DSP,TP212
  2. Fisher-support Vector Classifier,TP181
  3. Tracking of Moving Object Based on Multiple Instance Learning,TP391.41
  4. Image Classification and Annotation Based on Probabilistic Graphical Model,TP391.41
  5. The Research of Automatic Annotation Method for Natural Scene Image,TP391.41
  6. Combination Algorithm of the V-support Vector Machine,TP183
  7. Triplet Support Vector Machines for Pattern Classification,TP18
  8. Research of Support Vector Machines in Quality Management,TB114.2
  9. Research on Differential Protection of Transformers Based on Artificial Neural Network,TM772
  10. Support vector regression analysis and its application in drug sales prediction,F426.72
  11. Research of Image Annotation and Retrieval Based on SVM,TP391.41
  12. Research of Stamping Capp-based Intelligence Mould Quotation System,TG385
  13. The Research of Visual Fatigue Estimated Method Based on ECG and Pulse Signal,TP391.41
  14. Research on Fault Diagnosis Based on Particle Swarm Optimization Least Squares Support Vector Machines,TP18
  15. Accelerating Typical SVM Algorithms Through CUDA Platform,TP18
  16. The Research Between Temperature and Structure Modal Frequency,U441
  17. Application of BP Neural Network and SVR in Investigation for Influence of Elements on Magnetic Properties of (Nd,Pr) FeB Permanent Magnet,TM273
  18. Study on the Novel Methods for the Prediction of Protein Families,Q51
  19. Multi-Task Learning in Conditional Random Fields for Chunking in Shallow Semantic Parsing,TP391.1
  20. An Interactive Framework for Web Image Annotation,TP391.41
  21. Combining Visual and Textual Information for Automatic Image Annotation,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