Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision - Joko Siswantoro; Anton Satria Prabuwono; Azizi Abdullah; Bahari Indrus (Journal of ICT Research and Applications, 2017)
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.