Human Fingerprint Recognition System (HFRS) For Real-Time Application Using Support Vector Machine (SVM)
Human fingerprint recognition is a significant task for social communication. At present human fingerprint recognition has been used extensively, such as an authentication means of mobile phone usage, laptop and a checking for working hours. However, the human fingerprint recognition performance measure of existing system low. This paper presents human fingerprint recognition system (HFRS) deployments and many challenges are continue to arise in each one module phases including together with fingerprint image preprocessing, fingerprint detection, FHOG feature extraction and human fingerprint image recognition. The tests are processed out on the real time human fingerprint dataset using Support Vector Machine (SVM) with Radial Basis Function (RBF) and polynomial kernels. Experimental results represent the top most performance on the RBF kernel recognition (98.6%) when equate to the polynomial kernel (97.9%). The most important participation of this projected effort is to ensure the purpose of incremental SVM techniques to recognize human fingerprint for different group of student and faculty in college campus.