Implementation of Two-Dimensional Image Result Analysis Using Artificial Neural Networks with the Counter propagation Method

Two-dimensional image recognition is one of the activities to check the original image. The method counter propagation used is focused on how to extract data from the available samples. The data extraction step was dividing the sample into several research areas. Then from each region the active pixel value is taken so that numerical data can be obtained as much as the available area. The numerical result data is then normalized by fixed compare, where each numeric data comes from the same data.To prove the method, the writer made a supporting application, namely char-cognition with a basic visual programming language. The final result of the analysis shows that the pattern produced by this method can be recognized well the authenticity of the two-dimensional image. Manual examination is considered inefficient because it faces problems with the eye's eye foresight and accuracy. Two-dimensional images are generally identical but not the same in terms of shape and slope. Automatic two-dimensional image matching via a computer system is essential for better and more accurate identification of two-dimensional images. Artificial neural network method is used for extraction with various data in two-dimensional images.From the five of the simulation can be concluded that the best Learn Rates by the lowest Error Level is 0.1 and the best Learn Rates based on the highest Match Level is 0.3. Otherwise, due to successful rate from this experiment is not measured by low rate of Error Level but from the high of Match Level rate, so that Simulation 2 with Learn Rates=0.3 that will be used in the next experiment.