Iris Recognition Method Based on Quantum Parallelism and Grover Algorithm

Abstract

Abstract Traditional iris recognition method has low speed and searching rate under large-scale unstructured database background, it needs N/2 times to find the result when the database has N irises, and the probability of success is 1/2. An improved recognition method based on quantum parallelism and Grover quantum search algorithm is proposed. The feature vector's encoding and Hamming distance are extracted through twice calculations by using quantum parallelism. The Oracle operator in Grover algorithm is improved. The improved Oracle operator includes two databases. The database one contains four registers: index register, quantum bit register which includes target iris Hamming distance, data register, one quantum bit register. Database two includes all the Hamming distance. Compared with traditional recognition method, the proposed method just needs to apply N operations, the target iris location can be found from iris database. The simulation results show that the proposed method decreases the number of repetitions and effectively improves the search speed.