Detection and Classification of Damage in Fingerprint Images Using Neural Nets

The aim of this bachelor thesis is to study and design algorithm for detection of fingerprint damage caused by skin disease, specifically by wart and dyshidrosis. Symptome detection was implemented by convolutional neural network based on Keras framework. This network determine, which part of finger is damaged and in these areas will classify the disease. Combination of synthetic and real fingerprints was used to train the neural network