Recognition Between Eudiscoaster and Heliodiscoaster Using Competitive Neural Network


This research is aimed to design an Eudiscoaster and Heliodiscoaster recognition system. There are two main steps to verify the goal. First: applying image processing techniques on the fossils picture for data acquisition. Second: applying neural networks techniques for recognition.
The image processing techniques display the steps for getting a very clear image necessary for extracting data from the acquisition of image. This picture contains the fossils. The picture should be enhanced to bring out the pattern. The enhanced picture is segmented into 144 parts, then an average for every part can easily be computed. These values will be used in the neural network for the recognition.
For neural network techniques, Competitive neural network was used for comparisons. The weights and output values will be stored to be used later in identification. The Competitive network succeeded in identification and attained to (False Acceptance Rate = 15% - False Rejection Rate = 15%).