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Multi-layer neural network with single hidden layer and single output layer for back-propagation algorithm.
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Fingerprint authentication process plays a crucial role for human identifications. Fingerprint stored in the database are often used to confirm individual identity in cases like security checks, disaster, and medical jurisprudence. However, when dealing with the database consisting of a huge number of the fingerprint, recognizing the correct finger...
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... in our case, we considered implementing a neural network with three types of layers for the proposed fingerprint authentication system. Fig 2 illustrate the architecture of the proposed FAS with three neural network layers where the input layer receive the input vector consisting of downsampled pixel; the hidden layer and the output layer, which give the identified fingerprint image. 1) Input Layer: In the proposed method the input layer is considered as the the first layer of neural network and is used to input downsampled pixel from input fingerprint file thus it contains input vector for downsample pixel . ...
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Fingerprint & Palmprint are widely used biometric traits for human identification and authentication. Fingerprint & Palmprint Recognition Systems need feature images without background; this requires segmentation of input image. In this paper we have proposed a segmentation technique which is applicable for segmentation of both fingerprint and palm...
Citations
This paper presents an algebraic delay-independent stability (DIS) test for
the commensurate multiple time delay systems (CMTDSs). We provide necessary
and sufficient conditions for stability test. The stability is analysed using stability
tests of two univariate polynomials and a generalized eigenvalue problem. The proposed stability approach is advantageous compared to the existing methodologies
because it includes less computational complexity. Numerical examples are given to
demonstrate the applicability and effectiveness of the proposed approach.
The fingerprint identification has great effectiveness in forensic science and helps in the criminal investigations. Fingerprints are distinctive and remain enduring throughout a person’s life. The automatic fingerprint recognition systems are dependent upon hills and its characteristics known as minutiae. Hence, it is highly essential to score these minutiae accurately then refuse the improper parts. In this work a ridge ending and ridge ramify have been utilized as minutiae for fingerprint recognition system. At the time of analysis of algorithms, the approaches of attributes impart better results. The recognition rate is increased and the error rate is diminishing with the aid of this technique. The ultimate crucial stride here in matching of automatic fingerprint is to securely extractor specifics from the binary images of captured fingerprints. There are already a variety of techniques available to extract fingerprint details. The rate of recognition for such intended approach of fingerprint recognition system using artificial neural networks is 93%. From the extricate outcome, we may infer about a very affirmative impact of artificial neural networks on the comprehensive recognition rate, specifically in low excellence images.KeywordsFingerprint recognitionHuman fingerprintArtificial neural networksBack propagation
