Handwritten Character Recognition from Bank Cheque
Keywords:
Segmentation, Thinning, Scaling, Pattern matching, COG, complete Bipartite Graph, Adjacency matrixAbstract
Handwritten Character Recognition (HCR) is the ability of a computer to receive and interpret handwritten input captured by as digital cameras or other devices.Recognition of handwritten characters by computer is a serious problem because there are a many variety of writing styles, character shapes written by different individuals. The main objective of our project is to recognize the handwritten characters present in a bank cheque. Paper cheques still play a big role in the non-cash transactions in the world even after the arrival of credit cards, debit cards and other electronic means of payment. Huge volumes of handwritten bank cheques are processed manually every day in developing countries. The present cheque processing procedure requires a bank employee to read and manually enter the information present on a cheque (or its image) and also verify the entries like signature and date. An attempt is made in this project to recognize the characters present payee name and in the cheque amount by using image processing techniques on handwritten cheque images. The system uses broad steps like thresholding, image segmentation, thinning and pattern matching for extraction of characters. The pattern matching is done using graph based method. Graph matching techniques areintroduced to compute the similarity of characters extracted from bank cheque with theinformation of characters store in the database.
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