Many vision systems require text recognition captured at very high speed: vehicle registration identification devices, scanners, etc. Current technology enables the use of complex image pre-processing systems to enhance reading characteristics. This PhD thesis puts forward two binarisation algorithms that are suitable for high-precision applications in optical character reading (OCR). The binarisation of a digital image involves the conversion of the digital image into a black and white one in such a way that the essential properties of the image are conserved. Most reading recognition algorithms are written based on binary images.
A study of the various types of current voting systems, their advantages and drawbacks, was taken as the starting point.
Disadvantages present in the various types of voting systems were taken to be those involving security and privacy when casting a ballot as well as the user-friendly nature of the system. A second stage was to study the various current systems of binarisation and assessing their suitability to electronic voting applications.
Garazi Andonegi | alfa
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Drones can almost see in the dark
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