Open AccessPalmprint recognition using the cosine method
Author(s) -
Muhammad Kusban,
B Hari P,
Aris Budiman
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/674/1/012041
Subject(s) - biometrics , matching (statistics) , variance (accounting) , computer science , dimension (graph theory) , discrete cosine transform , preprocessor , pattern recognition (psychology) , artificial intelligence , field (mathematics) , identification (biology) , selection (genetic algorithm) , euclidean distance , value (mathematics) , data mining , mathematics , machine learning , statistics , image (mathematics) , botany , accounting , pure mathematics , business , biology
Palmprint Recognition Technology now requires breakthrough identification of diverse people. Palmprint recognition is the right choice of the system, namely the acceptance of biometrics that can be done quickly and cheaply because it has a significant enough media dimension that is difficult to manipulate. The four classifications of the biometric algorithm, the use of matching methods is still less attractive to researchers. In general, the part of the research concern is in the preprocessing and dimension reduction sections. Although researchers more widely use the Euclidean matching method, the selection of cosine methods is worth considering. The cosine method for the palmprint recognition matching process will have a significant effect on increasing the verification value when inserting the use of the contra-variance formulae in the equation. The selected amount of contra-variance is the data of the training. From the results of research that have been carried out, the rate of EER and verification are quite promising. The value of research results can compensate for other researchers in the same field.