Online Signature Slant Feature Identification Algorithm

According to the American National Science and Technology Council (NSTC), the first signature recognition system was developed in 1965. Then the research continued in 1970 focusing on the potential of geometric characteristic of a signature rather than dynamic characteristic. Nowadays, signature is a commonly used identification procedure. Everyone would be required having a signature for authorization and other important tasks that needs identification. Thus, signature has become one of a method to represent its writer uniquely. Signature has many hidden features that are difficult to extract. Some of the identified features that a signature should have are slanting, baseline, proportion and size. This paper covers the area of signature slant identification. Signatures are captured using a tablet and saved in a digitized format of x and y values. Then it is filtered and calculated for its angle and degree. In the end the signature will be classified to its slant category. A slant algorithm is created and coded into a functional system. An experiment consisting of 50 signatures are tested and the finding shows the angle and degree of the slant in every signature. The result is then tested for its accuracy with an available 10 sample of created proofed signatures. The result shows a favorable accuracy of 80% correct slant identification. The creation of this algorithm would be able to give some degree of contribution in the area of signature recognition. Key-Words: Slant, Slant Recognition, Signature Recognition, Online Signature, Curved Stroke, Curved Slant