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Thus, the channel decoder can decode the codeword only when the induced noise is small and the error is within the correcting capabilities of the channel code Otherwise, if the noise of the channel corrupts the signal, the resulting codeword cannot be decoded and the transaction is rejected as unauthorized Thus, the problem reduces to the estimation of the noise channel statistics and the exploitation of this a priori information at the channel decoder If the selected error correcting code is suitable for error protection on this channel, the decoder will decode X errorlessly Considering the above, the design of the system involves two critical parameters: r The error correcting performance of the channel code r The level of security of the biometric template s.

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On one hand, an encoder of high rate generates more parity bits, which increases the security of the template but also increases the risk of rejecting a genuine user On the other hand, a low rate encoder exhibits limited error-correcting capabilities andRelated: Create Barcode SSRS ASPNET , Print Barcode ASPNET , Barcode Generating RDLC NET Winforms.

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The feature vector x must be transformed from the continuous to the iscrete domain so that it can be further processed by the channel encoder This mapping can be represented by a uniform quantizer with 2L levels Each component of x is then mapped to an index in the set Q, through the function Q : Rk Qk , where Q = {0, 1, , L 1} The resulting vector q = Q(x) is fed to the Slepian Wolf encoder, which performs the mapping e : Qk Cn , where C = {0, 1} and outputs the codeword c = e(q), c Cn In this work, the Slepian Wolf encoder is implemented by a systematic LDPC encoder [25] LDPC codes were selected due to their excellent error detecting and correcting capabilities They also provide near-capacity performance over a large range of channels while simultaneously admitting implementable decoders.

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An LDPC code (n, k) is a linear block code of codeword length n and information block length k which is de ned by a sparse (n k) n parity matrix H, where n k denotes the parity bits produced by the encoder The code rate is de ned as r = k/n A code is a systematic code if every codeword consists of the original k-bit information vector followed by n k parity bits In the proposed system, the joint bit-plane encoding scheme of reference 26 was employed to avoid encoding and storing the L bit-planes of the vector q separately Alternatively, LDPC codes in a high-order Galois eld could be employed, but binary LDPC codes (GF(2)) were selected due to ease of implementation.

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Subsequently, the k systematic bits of the codeword c are discarded and only the parity bits s that is, the n k parity bits of the codeword c are stored to the biometric database Thus, the biometric template of an enrolled user consists of the parity bits s, s C(n k) and its size is n k s that is, the nk parity bits of the codeword c are NET Crystal barcode generatorin net Related: NET WinForms QR Code Generating Data, QR Code Generation VBNET , QR Code Generating ASPNET Size.

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Commitment. reading barcode with .net Using Barcode reader for . In this case, an error correcting code is used in order to associate a codeword c with person and to compute an offset ( = c x) for the biometric template x. The encrypted message (the fuzzy commitment) is then represented by the pair ( , h(c)), where h(c) is a one way hash function. It is worth noticing that neither the biometric feature nor the associated codeword is publicly stored. The authentication process is correctly performed if a fresh biometric reading y allows the computation of a binary string c = y suf ciently close to c so that the code decodes it to c and the comparison between their hash values succeeds. A similar construction has been proposed by Hao et al. [27], with the application of an iris code feature extraction algorithm and the combined use of Hadamard and Reed Solomon codes. .Related: QR Code Generating Word Size, VB.NET QR Code Generation Image, QR Code Generation .NET

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Control qr bidimensional barcode image with visual c# using barcode printing for net In our example with iris, the ECC is designed to encode 140 bits into 2048-bit codeword he redundancy rate of such ECC is quite high; 2048/140 = 1463 On enrollment, the codeword is simply XOR-ed with the iris template, and the resulting biometrically encrypted key is stored Neither the codeword nor the biometric template can be retrieved from the helper data, which is similar to a one-time-pad cryptosystem known in cryptography It is interesting to note that there are no speci c locations where the 140-bit key is hidden; it is dispersed over all 2048 bits On veri cation, a fresh 2048-bit iris template is obtained Some bits may have errors The fresh template is XOR-ed with the stored biometrically encrypted key If there were no errors, the original codeword would be obtained.

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However, since errors are unavoidable in biometrics, the result of the XOR will differ from the correct codeword Here the ECC decoder comes into play: If the number of errors is not too large, the ECC can correct all the errors and obtain the original codeword Since the codewords are deterministically mapped to 140-bit keys, the correct 140-bit key will be retrieved If, on the other hand, the number of errors exceeds the ECC s capability, the decoder will declare a failure Therefore, the output of BE algorithm is either a key or a failure message Ideally, the failure should be output for an impostor only; however, it could happen for a legitimate user as well that is, the system could have a false rejection, as in conventional biometrics As we can see, in the case of BE the ECC replaces a simple threshold-based Yes/No scheme of conventional biometrics.

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Designing a good (2048, 140) ECC for BE is itself a serious technological challenge, since the error rate for a biometric template is usually high Hao et al [31] used a combination of Hadamard (aka 1st order Reed Muller) and Reed Solomon ECCs Normally, a block ECC corrects up to 25% of errors in a hard decoding mode, which would be 511 errors in our example However, the authors ran the Reed Muller ECC in a soft decoding mode (ie, the decoder always outputs the nearest codeword, even in the case of possible failure), which allowed it to achieve better error-correcting capabilities To make sure that the algorithm always outputs the correct key (eg, in the soft decoding mode the ECC may output any key), a hashed value of the key is stored into the helper data, as shown in Figure 263.

integrating for java control to generate, create qr code 210 10 Java barcode makeron java using java topaint In a first empirical performance analysis, we have ompared the user interface over a database of half a million objects using a transient version (that loaded serialized data at initialization time), an orthogonally persistent version, and an orthogonally versioned version The response time of the navigation and update of the company graph was quite similar in all three versions We attribute this favorable result to the high overhead of the Swing interface that helped to overshadow the read and write barrier overhead of the persistent versions We have also evaluated the performance of the key underlying system OPJ The primary role of OPJ is as a persistent object system, so we compare it here against a number of alternative systems using a standard OODBMS benchmark, OO7 [Carey 1993].

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You can use WIA library to control the scanning process and tesseractdotnet for OCR . An updated . NET 4.0 version can be found here.












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