An Alternative to SOCIFS Writer Identification Framework for Handwritten Authorship

The uniqueness of shape and style of handwriting can be used to identify the significant features in confirming the author of writing. Acquiring these significant features leads to an important research in Writer Identification (WI) domain. This paper is meant to explore the usage of improved discretization method and explore an alternative to Cheap Computational Cost Class-Specific Swarm Sequential Selection (C₄S₄) WI framework for Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS) feature selection technique in order to find the unique significant features. This paper proposes a novel feature selection framework for handwritten authorship. The promising applicability of the proposed framework has been demonstrated and worth to receive further exploration in identifying the handwritten authorship.