Design of Offline and Online Writer Inference Technique
R. Raja Subramanian1, Ramalakshmi Ramar2
1R. Raja Subramanian, Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Virudhunagar (Tamil Nadu), India.
2Ramalakshmi Ramar, Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Virudhunagar (Tamil Nadu), India.
Manuscript received on 08 December 2019 | Revised Manuscript received on 20 December 2019 | Manuscript Published on 30 December 2019 | PP: 833-837 | Volume-9 Issue-2S2 December 2019 | Retrieval Number: B11291292S219/2019©BEIESP | DOI: 10.35940/ijitee.B1129.1292S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Writer inference systems tend to identify and verify the authorship of the handwritten documents. Each writer will have his own style of writing that uniquely identifies the writer. Hence authorship identification finds its application in forensic document analysis. It is also considered as one of the biometric features of a person, so helps in security to uniquely identify a person. Recognition of writers online has its application in detecting the identity thefts. That is compromising one’s social media account and sending messages to others as if he were an authentic sender. By discriminating the writing characteristics of the original and intruder, the masquerader can be identified. In this survey various works contributing to feature extraction and prediction of writers are discussed.
Keywords: Authorship identification, Run Length Features, Image Transforms, Writer Prediction.
Scope of the Article: Digital System and Logic Design