A technique of optical pattern recognition that combines the performance of a wavelet transformation and a multilevel composite filter is proposed. The essential advantage of this technique is distortion invariance. We show by digital simulation that this technique can successfully identify and discriminate complex biometric images, such as fingerprints distorted digitally by various types of distortions: rotation (up to 10 deg clockwise and counterclockwise), shift (up to 10% of the image size), occlusion, scaling (changes up to 5%), and pinch and punch (changes up to 10%). The wavelet transform is used for extracting crucial ridge information from tested images and eliminating its redundancies. The multilevel composite filter is generated by a simulated annealing algorithm.