Effects of fingerprint recognition algorithms on toeprint and fingerprint
Author(s): Obaje Samuel Enemakwu
Abstract: Democracy is a form of government in which politicians are chosen by popular vote. Voting may be done using behavioural biometrics, known as transparent balloting, which involves indicating a candidate of preference by indication, or physiological biometrics, known as hidden balloting, which involves appending a fingerprint to a vote. In certain countries around the world, fingerprints are used to cast ballots. However, injury casualties, natural disaster victims, and lepers, who account for one out of every 10,000 people in the world's population of approximately 7.7 billion, may pose a concern if their fingerprints are used to classify them. Two photographs were chosen to make up the sample collection: a Toeprint image with a left loop to be contrasted with a fingerprint image with a left loop. The photos were subjected to the standard fingerprint recognition algorithm, which included processes such as Normalisation, Orientation, Binarization, Thinning, and Minutiae Extraction. Since the experiment was not designed to measure the accuracy of the recognition algorithm, processing time and image quality were not taken into account. When the findings were compared, it was discovered that the algorithm had the same impact on both photos and that the derived minutiae points, which are the foundation for successful matching, were greater than 100. A modern method of self-identity and voting for lepers and injury patients is now accessible.