OBJECT RECOGNITION BY USING ARTIFICIAL NEURAL NETWORK: Turning point based shape recognition using NN

• Main Author: ABDULRHMAN IDRIS, MALIK ABDALLHA OSMAN
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi PETRONAS 2008
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/9995/1/2008%20Bachelor%20-%20Object%20Recognition%20using%20Artificial%20Neural%20Network%20%28ANN%29.pdf; http://utpedia.utp.edu.my/9995/

An artificial neural network (ANN) classifier for recognizing an object based on their shapes is presented, regardless their position, orientation or size. To extract features of an object, the significant point on the object known as comer or break point is extracted and the object shape is approximated by connecting this extracted break point with straight line. Shape features are associated with each segment consisting of three successive break points, or any two lines in the approximated shape. These features are the ratio between any two adjacent lines and the angle between them. The extracted features are used as input the ANN. The neural network configuration used in this project is multi-layer perceptron using back-propagation learning algorithm. In this project two type of shape have been recognized by a MLP. The network performance is evaluated by presenting several examples to the network and determines the difference between the tested image and the original shape used in the training, until the differences are minimized.