Broken Stick Regressive Convolution Neural Learning based Blood Group Detection with Fingerprint Images

Fingerprints are the accurate method for identifying an individual. Blood group detection is an essential medical diagnostic for guaranteeing the compatibility and prenatal care. Different researchers carried out their research on blood group detection with fingerprint images. But accuracy level was not improved and time consumption was not reduced by existing methods. In order to address these issues, a new deep learning model called Broken Stick Regressive Convolution Neural Learning (BSRCNL) Method is introduced. The main objective of BSRCNL method is to perform efficient blood group detection with fingerprint images to enhance accessibility, efficiency and ease of blood type identification.