Detecting Brazilian Real Banknotes under Various Lighting and Background Conditions

The detection and classification of banknotes can make life more accessible for visually impaired individuals. This paper aims to propose a method for segmenting Brazilian Real banknotes in images with varying backgrounds and lighting conditions, using an adaptive pre processing approach. The methodology includes adaptive histogram analysis and modification in the V channel, followed by the application of the Sobel filter to identify contours and segment the region of interest. A set of 72 new images made available was used to evaluate the effectiveness of the approach, that achieved an accuracy of 98.2% in detecting the banknote region under different backgrounds and lighting conditions. The research presents an effective approach to minimizing the effects of lighting while preserving the edge characteristics of the banknotes.