MODEL CERDAS PENGENALAN POLA WARNA MENGGUNAKAN ARSITEKTUR BAM KONTINU BERBASIS NEURAL NETWORK

Abstract

Color pattern recognition is an important field in digital image processing that has various applications, such as in object identification systems, image classification, and computer-based visual recognition. This study aims to design and implement a color pattern recognition system using Artificial Neural Networks (ANN) with the continuous Bidirectional Associative Memory (BAM) method. The continuous BAM method was chosen because of its ability to perform a bidirectional association process between input patterns and target patterns adaptively and stably. The research stages include collecting color data in RGB format, normalizing input values, forming an association matrix, training the network, and testing the system on a number of predetermined color patterns. The test results show that the continuous BAM model is able to recognize color patterns with a fairly high level of accuracy and a relatively fast convergence time. This system also shows resilience to small changes in color intensity values, so it has the potential to be applied to image recognition applications that require accurate color identification. Of the four color patterns resulting from the calculation, there are 2 patterns that match the target, namely the red and blue color patterns with the final target values [-1,1] output [-6,6] and [-1,-1] output [-6,-18].