Distortion of fingerprint is one of the important factors resulting in a false non-match, which may cause a bad effect on fingerprint applications, especially on a personal identification. Reasons for the fingerprint distortion are shown as follows: 1) a finger skin has an elasticity; 2) the finger is not flat; 3) during a fingerprint collection, a collector may use a lateral force or torque, and particularly when the lateral force or torque is too large, the fingerprint may be distorted severely.
There are four common methods for processing a distorted fingerprint in prior art.
A) A fingerprint sensor is reasonably designed and the collector is required to operate reasonably. However, this method has following defects: 1) the fingerprint which has been collected cannot be processed; 2) in practice, the collector should collect the fingerprints according to strict steps, which results in the low efficiency; 3) a distorted fingerprint resulted from a distortion of the skin itself (for example, the skin becomes wrinkled after putting it into water for a while) cannot be dealt with.
B) A hardware device is used to detect the distortion. For example, a pressure sensor is disposed under the collecting plane of a fingerprint collection instrument. The method has following defects: 1) a specific pressure sensor is required, which increases the cost of the hardware device; 2) the distorted fingerprint which has been collected using traditional sensors cannot be processed; 3) a distorted fingerprint resulted from a distortion of the skin itself cannot be dealt with.
C) A software device is used to detect the distortion. It is determined whether the fingerprint is distorted via a statistical learning method according to the difference in appearance between the distorted fingerprint and the normal fingerprint. However, with this method, the distorted fingerprint can only be detected, but cannot be matched to the normal fingerprint.
D) A certain distortion is allowed during the matching stage. A threshold for the distortion is set in the fingerprint matching algorithm, and in order to deal with the severe distortion, the threshold should be large enough. However, minutiae which should not be matched with each other may be matched with each other due to the large threshold, such that the similarity between the unmatched fingerprint pairs is increased.
A distortion rectification refers to converting the distorted fingerprint into the normal fingerprint. The distortion rectification is more complex than the distortion detection, because the distortion detection only needs to predict a two-valued variable but the distortion rectification needs to predict a distorted field which is a high dimensional vector, although the distortion rectification and the distortion detection have the same input (i.e., a fingerprint image). Therefore, it is difficult for the distortion rectification, and an effective method has not been proposed so far.