Classification of thumbprint using Artificial Neural Network (ANN) / Nurafizah Zakaria

This thesis presents the classification of thumbprint using Artificial Neural Network (ANN); The ANN technique is implemented in order to improve the minutia extraction techniques. The classification of thumbprint is used in order to match the person's identification and train the data by using ANN. The data of thumbprint is taken from five different people. For each person, 30 thumbprint data is taken. All the data will be the input for artificial neural network for learning purposes. All the data will be adjusted using Corel. Then by using Matlab software, the data is trained and tested according to the artificial neural network program; This is to ensure that the output is matched with the input data. This is shown in a graph whether the system is sufficient enough of training the thumbprint data. It can also be used effectively in order to classify the person identification. Therefore, the result shows that the system is highly accurate in training the data. For further enhancement the overall system to identify the person identification should be developed.