Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision
| Main Authors: | Siswantoro, Joko, Prabuwono, Anton Satria, Abdullah, Azizi, Bahari, Idrus |
|---|---|
| Format: | Article PeerReviewed application/pdf |
| Terbitan: |
TB Journal Publisher, LPPM – ITB
, 2017
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| Subjects: | |
| Online Access: |
http://repository.ubaya.ac.id/31233/1/Paper%20J%20ICT%20Res%20App.pdf http://journals.itb.ac.id/index.php/jictra/issue/view/540 http://repository.ubaya.ac.id/31233/ |
Daftar Isi:
- 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.