Automatic Character Recognition has wide variety of applications such as automatic postal mail sorting, number plate recognition and automatic form of reader and entering text from PDA's etc. Cursive script’s Automatic Character Recognition is a complex process facing unique issues unlike other scripts. Many solutions have been proposed in the literature to solve complexities of cursive scripts...

This paper presents experiments on Optical character recognition (OCR) as a combination of Ocropy software and data-driven spelling correction that uses Weighted Finite-State Methods. Both model training and testing were done on Finnish corpora of historical newspaper text and the best combination of OCR and post-processing models give 95.21% character recognition accuracy.

Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. Basically, OCR technique converts images into editable format. This technique converts images in the form of documents such as we can edit, modify and store data more safely for longt...

The collaboration of the network and optical character recognition (OCR) is expected to be useful for extending the applications of OCR, and it has a potential to open up new vistas in future services using OCR. We presented the basic ideas of the synergetic OCR system in 2004, and developed a platform called WeOCR to realize the web-based OCR services. The number of accesses has been increasin...

Character Segmentation is the most crucial step for any OCR (Optical Character Recognition) System. The selection of segmentation algorithm being used is the key factor in deciding the accuracy of OCR system. If there is a good segmentation of characters, the recognition accuracy will also be high. Segmentation of words into characters becomes very difficult due to the cursive and unconstrained...

• Recognition of logical document structures [1], where knowledge of the font used in a word, line, or text block may be useful for defining its logical label (chapter title, section title or paragraph). • Document reproduction, where knowledge of the font is necessary in order to reproduce (reprint) the document. • Document indexing and information retrieval, where word indexes are generally p...

Optical Character Recognition (OCR) is the technique which enables a machine to automatically recognize the characters or scripts written in the users’ language. Optical Character Recognition (OCR) has become one of the most successful applications of technology in the field of pattern recognition and artificial intelligence. In this project a scanned image is translated into machine editable t...

Optical character recognition (OCR) method has been used in converting printed text into editable text. OCR is very useful and popular method in various applications. Accuracy of OCR can be dependent on text preprocessing and segmentation algorithms. Sometimes it is difficult to retrieve text from the image because of different size, style, orientation, complex background of image etc. We begin...

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 ...

Improvements and new developments in the field of Artificial Intelligence have opened new horizons in the advancement of machines that originally have limited intelligence. As compared to human brain, machines have already better computational speed and storage however there is still much room to improve the capability to acquire and process data and draw conclusions from it on its own. Optical...