Malaysian Banknote Reader Featuring copyright Detection Using Fuzzy Logic Weighted Specific (FLWS) Algorithm

Malaysian Banknote Reader Featuring copyright Detection Using Fuzzy Logic Weighted Specific (FLWS) Algorithm

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To identify fake Malaysian banknotes, this research suggested a revolutionary fuzzy logic weighted specific Skin Care Tools (FLWS) approach in image processing techniques.The FLWS Algorithm has the benefit of a more accurate model because it is a human guidance learning algorithm that demands training to obtain the precise weights for each security feature.The trial outcomes also demonstrated that, for the purpose of detecting copyright Malaysian banknotes, the FLWS model outperformed the parallel fuzzy logic weighted averaging Pleasure Saddle (FLWA) algorithm, MobileNet model, and VGG16 model.Its adoption of well-known watermark features, with specific weights assigned, and well-known machine learning techniques to distinguish between genuine Malaysian banknotes and copyright Malaysian banknotes gives it a clear advantage over earlier or current banknote copyright detection techniques.