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Difference between revisions of "Malappuram/MESCE/Malayalam OCR"
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Welcome to Akshara Malayalam O.C.R. This is a "Character" recognition software which can be used to recognize malayalam printed texts etc. It is | Welcome to Akshara Malayalam O.C.R. This is a "Character" recognition software which can be used to recognize malayalam printed texts etc. It is released under "GNU General Public License" and uses "IPL98" and "WxWidgets" libraries. It is a "Cross Platform Open Source" project started by the students of MES College of Engineering, Kuttipuram. | ||
The OCR software has been developed in response to save time, the most valuable resource that we have. OCR has been designed to automate the process of conversion of printed matter, may it be books, magazines or even documents. | The OCR software has been developed in response to save time, the most valuable resource that we have. OCR has been designed to automate the process of conversion of printed matter, may it be books, magazines or even documents. | ||
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Any OCR implementation consists of a number of preprocessing steps followed by the actual recognition. The number and types of preprocessing algorithms employed on the scanned image depend on many factors such as age of the document, paper quality, resolution of the scanned image, the amount of skew in the image, the format and layout of the images and text, the kind of script used and also on the type of characters - printed or handwritten. The recognition stage usually involves calculating a number of statistical parameters and hence recognizing the character. Typical preprocessing stages include noise cleaning, binarization, skeletonization, skew detection and correction and feature extraction - like line and word segmentation. | Any OCR implementation consists of a number of preprocessing steps followed by the actual recognition. The number and types of preprocessing algorithms employed on the scanned image depend on many factors such as age of the document, paper quality, resolution of the scanned image, the amount of skew in the image, the format and layout of the images and text, the kind of script used and also on the type of characters - printed or handwritten. The recognition stage usually involves calculating a number of statistical parameters and hence recognizing the character. Typical preprocessing stages include noise cleaning, binarization, skeletonization, skew detection and correction and feature extraction - like line and word segmentation. | ||
* [http://sourceforge.net/projects/akshara Project page on sourceforge] | |||