The Uniformly Random Permutation Hashing (URP-IoM) algorithm demonstrates reliable performance and irreversibility in biometric template protection. However, URP-IoM, through random permutation and Hadamard product computation, fails to retain the local features of the original feature vector, which can negatively impact recognition rates and result in varying performance across different datasets. Addressing the impact of biometric template revocability on recognition rates and performance, this paper proposes a novel revocable template method for fingerprint biometrics, called Variable Window-Based Random Permutation IoM Hashing &&Check Code (VWP-IoM &&CC). This method first generates variable windows and check codes based on the Euclidean features of the user password and original feature vector, then records the maximum index of the Hadamard product under the variable window. Finally, it combines the maximum index value with the check code. Experimental results show that the VWP-IoM &&CC algorithm improves recognition rates and performance in FVC2002 and FVC2004 (DB1, DB2), and also meets the requirements of revocability and unlinkability.