*Professor & Head, Department Electronics and Communication Engineering, Abdulkalam Institute of Technological Sciences, Kothagudem, Andhra Pradesh, India
**Associate Professor, Electronics and Communication Engineering, Abdulkalam Institute of Technological Sciences, Kothagudem, Andhra Pradesh, India
***Assistant Professor, Electrical and Electronics Engineering, Abdulkalam Institute of Technological Sciences, Kothagudem, Andhra Pradesh, India
Online published on 11 April, 2014.
Handwriting-based writer identification is a hot research topic in the pattern recognition field. Now a day, person identification has become a major problem to counterfeit the forgery. The identification of a person on the basis of scanned images of handwriting is a useful biometric modality with application in forensic and historic document analysis and constitutes an exemplary study area within the research field of behavioral biometrics. Writer recognition is the task of determining the author of sample handwriting from a set of writers and verifying the writer from the sample. Text-independent offline writer recognition is more challenging than online writer recognition. Here we purpose a system which extracts the simple writer specific features from the scanned character images written by different writers and use them to recognize the writer.
Offline character handwriting recognition, Neural Network, Training the system, Testing the system
