Product Identification Using Image Processing And Radial Basis Function Neural Networks - Khairul Azha , A. Aziz; Abdul, Kadir; Rostam Affendi, Hamzah; Amat Amir , Basari (Trans Tech Publications, Switzerland, 2015)
This paper presents a product identification using image processing and radial basis function neural networks. The system identified a specific product based on the shape of the product. An image processing had been applied to the acquired image and the product was recognized using the Radial Basis Function Neural Network (RBFNN). The RBF Neural Networks offer several advantages compared to other neural network architecture such as they can be trained using a fast two-stage training algorithm and the network possesses the property of best approximation. The output of the network can be optimized by setting suitable values of the center and the spread of RBF. In this paper, fixed spread value was used for every cluster. The system can detect all the four products with 100% successful rate using ±0.2 tolerance.