This paper proposes algorithms to localize vehicle number plates from natural background images, to segment the characters from the localized number plates and to recognize the segmented characters. The reported system is tested on a dataset of 560 sample images captured with different background under various illuminations. The performance accuracy of the proposed system has been calculated at...

This paper proposes a system for recognizing numeric strings from topographical maps, which is composed of the automatic recognition stage and the interactive recognition stage. In this method, uncertain numeric strings extracted through the automatic recognition stage based on topographical map feature only, are confirmed and corrected by the interactive recognition stage. Therefore we can obt...

OCR often performs poorly on degraded documents. One approach to improving performance is to determine a good filter to improve the appearance of the document image before sending it to the OCR engine. Quality metrics have been measured in document images to determine what type of filtering would most likely improve the OCR response for that document image. In this paper those same quality metr...

Optical character recognition refers to the process of translating segmented hand-written images or typewritten images into machine editable text. In this study, we propose a Tamil palm leaf manuscripts character recognition system using FFBNN technology. First the palm leaf manuscripts characters are segmented by exploiting the sliding window and adaptive histogram calculation. Afterwards, the...

The document images that are fed into an Optical Character Recognition system, might be skewed. This could be due to improper feeding of the document into the scanner or may be due to a faulty scanner. In this paper, we propose a skew detection and correction method for document images. We make use of the inherent randomness in the Horizontal Projection profiles of a text block image, as the sk...