Traits, namely, gender, nationality, age, height, gait, etc., are popular in the field of biometric applications. This is because traits prediction helps biometric methods to improve their performances by reducing the complexity of the problem. In addition, traits prediction plays a vital role for forensic applications and security by helping in identifying suspicious behaviors.
handwriting analysis has now reached beyond traditional boundaries such as emotions, nationality, gender, age and other traits prediction. Due to large variations in handwriting, ink, pen, paper, script, age, gender and individual difference, it is not so easy to identify traits based on handwriting analysis. This work focuses on nationality and ethnicity identification as it is useful for identifying crimes.
English writing by different people can be compared. People originating from India and Bangladesh can expect more cursive than straightness compared to Chinese. Since all the citizens of respective nations follow their own scripts, we can expect different English writing.
Handwriting2
A New COLD Feature based Handwriting Analysis for Ethnicity/Nationality Identification