Improvement in twin handwriting identification with invariants discretization

Abstract

One of the most popular areas of study in pattern recognition which has now become the centre of many researchers' attention is Writer Identification. A more recent development in the area is Twins Handwriting Identification which has now become not only an important, but also widely popular area of study especially in the fields of forensic research and biometrical identification. In terms of biometrical identification, it is known that a pair of twins may share various similar traits genetically. Forensic evidence can be easily obtained from handwriting samples. Therefore, in order to achieve reliable and accurate identification based on handwriting, it is important for the similarities in the writing traits of a pair of twins to be differentiated. In identifying an individual, handwriting style can be analyzed to allow the implicit representation of the unique hidden features of the individual's handwriting. Said unique features can help in identifying the writer of the text which can be essential when identifying the writer between a pair of twins. Previous studies in authorship identification were highly concentrated in the study of the classification task as well as features extraction. However, the issue of the similarities in the traits of a pair of twins' handwriting were not taken into account thus, leaving a high possibility of degrading the performance of the classification process. Therefore, in order to achieve better input for the classification task, this article will discuss an additional process which can better represent an individual's personal features through the transformation of the similarities via discretization protocol. The additional process can help improve the level of identification for Individuality of Handwriting of a pair of twins.