Minutiae vicinity [1] captures a fingerprint's local topological information among neighboring minutiae for biometric template protection. We extend in this paper the definition of a minutia vicinity to a general one, which deems the conventional definition as a special case. Under this generalized definition, multiple vicinities can be obtained via defining different radial distances from one central minutia. Then fusion of these multiple vicinities can be done for better biometric performance. We present a score-level fusion rule which assigns match cases to different match voting layers and weighs them according to their ranking in posterior probability of a genuine match. Experiments achieve an average EER=0.0143 (compared to EER=0.0252 in the single vicinity case [1]) over the database FVC2002 DB2_A under the token-stolen scenario i.e., using the same public transformation parameters when generating protected vicinities for comparison.