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논문검색

Structural Characterization of Worm Images Using Trace Transform and Backpropagation Neural Network

초록

영어

Various diseases caused by pathogenic parasites and fungi may be characterized by shape based structures. No significant attempt has been made so far to categorize such parasites by their shape properties, which can make the task of information retrieval much easier than annotating all of them separately. Here we present an automatic classification system which can retrieve the parasite or fungi’s information from the database using shape based information. To reduce time complexity of the information retrieval parasites having more or less identical shapes are clustered in the same group. A set of shape descriptors, generated by trace transform has been used to characterize structure of worms. Backpropagation neural network is trained, which leads to 85.71% accuracy of classification using statistically significant shape features.

목차

Abstract
 1. Introduction
 2. Materials
 3. Shape-based Worm Image Retrieval
  3.1 Image segmentation
  3.2.1 Convexity
  3.3 Statistical Analysis
 4. Classification Using Error Backpropagation Neural Network
  4.1 Sensitivity Analysis
 5. Results and Discussion
 6. Conclusions
 References

저자정보

  • Chandan Chakraborty School of Medical Science & Technology Indian Institute of Technology Kharagpur

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