Character Recognition and Document Handling in Banks

Optical Character Recognition from Degraded Document Images

Segmentation of the text from badly degraded document images is very challenging tasks due to the high inter/intra variation between the document background and the foreground text of different types of document images. In this paper, a novel document image binarization technique is used to addresses the issues in the degraded document images by using adaptive image contrast. The adaptive image...

Transductive Learning for Document Classification and Handwritten Character Recognition

Degraded Document Image Binarization Using Optical Character Recognition

The proposed OCR algorithm to retrieve the text in the scanned document images. Here the text detection algorithm based on two machine learning classifiers: one allows generating candidate word regions and the other filters out non-text ones. The extract connected components (CCs) in images by using the maximally stable extremal region algorithm. In CC clustering adaboost classifiers are used t...

Handwritten Kannada Document Image Processing using Optical Character Recognition

The objective of Optical Character Recognition (OCR) is automatic reading of optically sensed document text materials to translate human-readable characters to machinereadable codes. In Optical Character Recognition, the text lines in a document must be segmented properly before recognition. English Character Recognition (CR) has been extensively studied in the last half century and progressed ...

A Simplified Method for Handwritten Character Recognition from Document Image

This paper presents a simple and effective technique for converting handwritten textual character from paper document into machine readable form. The proposed method takes the scanned image of the handwritten character from paper document as input and shows the recognized character as its output. Using this method, the object in the converted binary image is segmented and is resized in a global...