Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision

Siswantoro, Joko and Prabuwono, Anton Satria and Abdullah, Azizi and Bahari, Idrus (2017) Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision. Journal ICT Research and Applications, 11 (2). pp. 184-198. ISSN 2338-5499

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Official URL: http://journals.itb.ac.id/index.php/jictra/issue/v...

Abstract

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.

Item Type: Article
Uncontrolled Keywords: Kalman filter; linear model; natural produce; neural network; recognition
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering > Department of Informatic
Depositing User: Joko Siswantoro
Date Deposited: 13 Sep 2017 07:39
Last Modified: 13 Sep 2017 07:39
URI: http://repository.ubaya.ac.id/id/eprint/30721

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