Signature Extraction and Recognition from Bank Cheque Image
Bramara Neelima K, S Arulselvi2
1Bramara Neelima K*, Research Scholar, Department of Electronics and Communication Engineering, Bharath Institute of Higher Education and Research, Chennai, India.
2S Arulselvi, Research Supervisor, Associate Professor, Department of Electronics and Communication Engineering, Bharath Institute of Higher Education and Research, Chennai, India
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2211-2214 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7766129219/2019©BEIESP | DOI: 10.35940/ijitee.B7766.129219
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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: Automatic signature extraction and recognition from document images is an open research problem. Signature verification is of two types; static and dynamic, and has two approaches; writer dependent and writer independent. Signature verification system in case of bank cheque image should essentially be an error prone system to elude the fraudulent transactions. In this work, a three layer signature verification system is proposed, which is writer independent and offline signature verification system. Graphometrical and FAST features are extracted from the signature images and are given as inputs to the classification algorithms. The proposed signature verification model is a combination of three classification algorithms; artificial neural network, Gaussian mixture model and image matching models, to circumvent the fraudulent transactions. The overall performance accuracy of proposed process is 99%.
Keywords: Signature Verification, Document Analysis, Artificial Neural Network.
Scope of the Article: Image Processing and Pattern Recognition