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文章基本信息

  • 标题:Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision
  • 作者:Joko Siswantoro ; Anton Satria Prabuwono ; Azizi Abdullah
  • 期刊名称:Journal of ICT Research and Applications
  • 印刷版ISSN:2337-5787
  • 电子版ISSN:2338-5499
  • 出版年度:2017
  • 卷号:11
  • 期号:2
  • 页码:185-199
  • 语种:English
  • 出版社:Institut Teknologi Bandung
  • 其他摘要:Natural produce recognition is a classification problem with various applications in the food industry. This paper proposes a natural produce recognition method using computer vision. The proposed method uses simple features consisting of statistical color features and the derivative of radius function. A hybrid neural network and linear model based on a Kalman filter (NN-LMKF) was employed as classifier. One thousand images from ten categories of natural produce were used to validate the proposed method by using 5-fold cross validation. The experimental result showed that the proposed method achieved classification accuracy of 98.40%. This means it performed better than the original neural network and k -nearest neighborhood.
  • 其他关键词:Kalman filter;linear model;natural produce;neural network;recognition.
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