Abstract
Problem statement: The study on twins is an important form of study in the forensic and biometrics field as twins share similar genetic traits. Handwriting is one of the common types of forensic evidence. Differentiating the similarities of writing of a pair of twins is critical in establishing the reliability of handwriting identification. Writing style can be used as biometric features in authenticating individual uniqueness where these unique features can be used to identify the writer, including between a pair of twins. Existing works in Writer Identification concentrate on feature extraction and the classification task in order to identify authorship. The high similarity in a pair of twins’ handwriting may degrade classification performance. There should be some standards to represent these unique features before entering into the classification task which is with the use of discretization technique. Approach: We proposed a new framework for writer identification in terms of identifying twins’ handwriting and showed the effect of discretization process on handwriting samples of a pair of twins in order to obtain individual identification. Results: An experiment has been done at the Sulaimania University in Iraq with fourteen pairs of identical twins where each twin provides 4 samples of handwriting for the purpose of data collecting. These samples were implemented in this research making a comparison between the new proposed framework and classic framework. Conclusion: Our experimental results showed that with new framework identification of handwriting of a pair of twins can be improved through the discretization process.
Highlights
Pattern recognition serves as a vital part of various engineering and scientific fields such as computer vision, biology and artificial intelligence
Previous studies done on biometric identification of twins such as the discriminability between the fingerprints of a pair of twins (Jain et al, 2002), DNA analysis (Rubucki et al, 2001), computational discriminability analysis on the fingerprints of twins (Liu and Sargur, 2009), show of coefficient values in individual sets as a form of unique code for a person’s face (Rycchilk et al, 2009), prove that there are physiological traits in nature which do not change over the years
This study will adopt the Invariant Discretization technique based on the previous work done in (Muda et al, 2008) to be implemented on the twins’ handwriting
Summary
Pattern recognition serves as a vital part of various engineering and scientific fields such as computer vision, biology and artificial intelligence. A person’s handwriting is usually affected by many personal elements such as self training history plus physiological and psychological state and nature which makes distinguishing the handwriting of a pair of twins a form of study with utmost importance. The Twins Handwriting Identification is a quite popular area of research in pattern recognition and computer vision fields as it, in some situations, provide the only means of discovering the real writer of a written text out of a group of people (Plamondon and Lorette, 1989; Srihari, 2010). Previous studies done on biometric identification of twins such as the discriminability between the fingerprints of a pair of twins (Jain et al, 2002), DNA analysis (Rubucki et al, 2001), computational discriminability analysis on the fingerprints of twins (Liu and Sargur, 2009), show of coefficient values in individual sets as a form of unique code for a person’s face (Rycchilk et al, 2009), prove that there are physiological traits in nature which do not change over the years. Techniques have been established over the years, depending on human’s knowledge and proficiency to sort
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