Abstract
This paper present a new handwritten English word database namely, ISIHWD for off-line handwritten word recognition and writer identification. It is a collection of 62 English legal amount words used in Indian bank cheque written by 105 different writers. The database consist of 31124 handwritten words split into a training set of 24924 words and a test set of 6200 words to a provide common platform in writer independent word recognition. The database is evaluated by deep convolution neural network based feature with SVM classifier for writer independent handwritten word recognition and text dependent writer identification based on single word. Average word recognition and writer identification accuracy are achieved as 95.35% and 85.70% respectively.
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