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A PCNNs-based square-and-triangle-template method for binary fingerprint image thinning is proposed. The algorithm is iterative: combined sequential and parallel processing is employed to accelerate execution. When a neuron satisfies the square template, the pixel corresponding to this neuron will be noted during the process and be deleted until the end of the iteration; on the other hand, if a neuron meets a triangle template, it will be removed directly. In addition, this proposed algorithm can be effective for fingerprint thinning without considering the direction. The results showed that, with combined sequential and parallel conditions for border pixels removal, the algorithm could not only speed up the fingerprint thinning process, but also be applied to other common images. Furthermore, this algorithm might be applied to fingerprint identification systems to save time for identifying and eliminating spurious minutiae.