Hand-written signature identifying method based on PCA method

Abstract

The invention provides a hand-written signature identifying method based on a PCA method. The hand-written signature identifying method includes the steps of S1: obtaining original hand-written signatures, and storing the original hand-written signatures as signature images with uniform pixel format; S2: training the hand-written signature samples, taking the original signature images as an image training set, conducting gray processing for the images in the image training set and placing the processed images sequentially in a matrix, conducting special dimension reduction for images through the PCA method and extracting characteristic values and characteristic vectors to obtain the characteristic signature Y of the training sample set; S3:identifying a hand-written signature by using a nearest neighbor method, projecting the hand-written signature to be identified on a characteristic projection matrix U obtained from S2 to obtain a characteristic signature Y', comparing the characteristic signature Y' with the characteristic signature Y obtained from the training sample set through PCA projection, and selecting the minimal distance as a matching item. The recognition rate is high.

Description

technical field [0001] The invention relates to the image recognition technical field in the technical field of the Internet of Things, in particular to a handwritten signature recognition method based on PCA (Principal Component Analysis) algorithm. Background technique [0002] Signatures have always played an important role in marking identity, and are widely used in various fields of society. Everyone's signature has formed a unique style in the long-term signature, even if two people with similar handwriting, both Impossible to do exactly the same imitation. In the computer identification system, the development of identification methods based on individual biometrics is one of the best breakthroughs in the field of confidentiality. The biometrics that can be used as identification should theoretically have the following characteristics: [0003] Extensiveness, that is, everyone should have this characteristic; [0004] Uniqueness, the characteristics that each person...

AI Technical Summary

Problems solved by technology

For offline handwritten signature recognition, none of the dynamic information generated during the writing process can be retained. It can only be identified based on the static information of the signature image and the global and local characteristics of each person's handwriting. In this case, the identification is slightly more difficult.

Images