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Optical Character Recognition

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Optical Character Recognition

OCR is one among the aspects where technology focus is eyed on. Lots of researches have been progressing past decades and valuable findings has already been brought up. OCR extends its wings on numerous technologies and applications in market. Handwritten
character recognizer using Neural networks is a crucial facet that has a vital essence in mobile application world. As majority of the people in the world prefer and use the hand written content for information storage or document, the information has the restrictions limited to only the material where it is written. The computer world has
put in its hands to scan these content and image it thus finally capture the content in printed machine interpretative format. With the drastic improvement in mobile technology the document management is given importance for management of information.
Optical Character Recognition
Imagine writing an article using pen and paper and use mobile application as a tool to convert the handwritten material to a machine printed text only by a click and capture using camera. OCR using neural networks has the capability of extracting the
content separating the text word by word and then character by character and manipulate for character detection using certain algorithms and help in the conversion.
Typically understanding certain style of writing the text is essential. Everyone has their own style of writing. Understanding the styles is complex phenomenon when the character conversion is considered. This is where neural network is playing a key role. Considering the neural structure of the human body, we find the human body as simple as we see with our sense. But the internal architecture say a nervous system and its interconnections, the neural network is being developed understanding and following this nature. It is as simple as a pixel being accumulated in horizontal and vertical reference to define a picture. Here each pixel has a color to display. Similarly each of the interpretations made are accumulated and the collective information is analyzed and brought up to a conclusion. Similarly in neural networks each of the neurons interacts and interpret the information collected. OCR uses this phenomenon to bring out certain conclusions and make out character recognition.

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