首页    期刊浏览 2025年02月23日 星期日
登录注册

文章基本信息

  • 标题:Structural Characterization of Worm Images Using Trace Transform and Backpropagation Neural Network
  • 本地全文:下载
  • 作者:Chandan Chakraborty
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2012
  • 卷号:5
  • 期号:3
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:Worm images; shape descriptors; Hu moments; Trace transform; Back;propagation neural network
国家哲学社会科学文献中心版权所有