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OCR for .NET are hosted on GitHub. You can either clone the repository using your favorite GitHub client or download the ... tesseract ocr wpf Running the Sample Microsoft OCR Application - C# Corner
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Some kernel patches in particular can totally break the functionality of third-party commercial software, which may at best mean that you need to reconfigure the software and at worst could lead to a situation where you have real difficulty in getting back to a working system.Related: Create QR Code Java , Intelligent Mail Generator C# , .NET WinForms UPC-A Generation In addition, a Reed Solomon ECC encodes 32 seven-bit bytes to produce 20 seven-bit bytes that is, 140 bits in total On veri cation, the Reed Muller ECC is run in a soft decoding mode (ie, it always produces an output codeword rather than declaring a failure) in each chunk, yielding 32 seven-bit bytes The Reed Solomon (32B, 20B) ECC can correct up to 6-byte errors In total, two ECCs can correct about 25 27% of bit errors The key size of 140 bits is suf cient for most cryptographic applications The scheme showed excellent performance: FRR was only 047% at FAR = 0 (or less than 1 in 200,000) These are the best results achieved so far for a BE scheme, although the database of iris images was captured under close to ideal conditions However, certain nonrandomness of the iris template (ie. 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Define Data Matrix Printer Barcode. .Related: Code 128 Generation C# , Generate Codabar .NET , Excel QR Code Generator , 2048 bits have the entropy of 249 bits) and the small size of the Reed Muller block (64 bits) could be a source of potential security vulnerabilities (see Section 266) Bringer et al [48, 49] used a product of two Reed Muller ECCs (64,7) and (32, 6), to link a 42-bit key to the 2048-bit iris template They applied iterative (ie, soft) decoding This construction is near-optimal in the sense that it allows achieving the accuracy close to the theoretical limits: FRR = 56% at FAR < 10 5 for ICE iris database This database is more realistic than the one used by Hao et al Philips Priv-ID System Van der Veen, Kevenaar, Schrijen, Akkermans, and Zuo presented a BE system for face recognition [71] It is based on the fuzzyRelated: . 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