5,617 research outputs found
Signal Flow Graph Approach to Efficient DST I-IV Algorithms
In this paper, fast and efficient discrete sine transformation (DST)
algorithms are presented based on the factorization of sparse, scaled
orthogonal, rotation, rotation-reflection, and butterfly matrices. These
algorithms are completely recursive and solely based on DST I-IV. The presented
algorithms have low arithmetic cost compared to the known fast DST algorithms.
Furthermore, the language of signal flow graph representation of digital
structures is used to describe these efficient and recursive DST algorithms
having points signal flow graph for DST-I and points signal flow
graphs for DST II-IV
The study of probability model for compound similarity searching
Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model
ADAPTABLE FINGERPRINT MINUTIAE EXTRACTION ALGORITHM BASED-ON CROSSING NUMBER METHOD FOR HARDWARE IMPLEMENTATION USING FPGA DEVICE
In this article. a main perspective of developing and implementing fingerprint extraction and matching
algorithms as a pari of fingerprint recognition system is focused. First, developing a simple algorithm to
extract fingerprint features and test this algorithm on Pc. The second thing is implementing this algorithm
into FPGA devices. The major research topics on which the proposed approach is developing and
modifying fingerprint extraction feature algorithm. This development and modification are using crossing
number method on pixel representation value '0'. In this new proposed algorithm, it is no need a process
concerning ROI segmentation and no trigonometry calculation. And specially in obtaining their parameters
using Angle Calculation Block avoiding floating points calculation. As this method is local feature that
usually involve with 60-100 minutiae points, makes the template is small in size. Providing FAR. FRR and
EER, performs the performance evaluation of proposed algorithm. The result is an adaptable fingerprint
minutiae extraction algorithm into hardware implementation with 14.05 % of EEl?, better than reference
algorithm, which is 20.39 % . The computational time is 18 seconds less than a similar method, which takes
60-90 seconds just for pre-processing step. The first step of algorithm implementation in hardware
environment (embedded) using FPGA Device by developing IP Core without using any soft processor is
presented
Multibiometric security in wireless communication systems
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and
WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition.
First is the enrolment phase by which the database of watermarked fingerprints with
memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel.
Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present oneâs fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user.
The following three steps then involve speaker recognition including the user
responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user.
In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint
image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and
sliding neighborhood) have been followed with further two steps for embedding, and
extracting the watermark into the enhanced fingerprint image utilising Discrete
Wavelet Transform (DWT).
In the speaker recognition stage, the limitations of this technique in wireless
communication have been addressed by sending voice feature (cepstral coefficients)
instead of raw sample. This scheme is to reap the advantages of reducing the
transmission time and dependency of the data on communication channel, together
with no loss of packet. Finally, the obtained results have verified the claims
FINGERPRINTS PREPROCESSING USING WALSH FUNCTIONS
Minutiae classification and fingerprint classification in fingerprint evaluating process are very important. Fingerprint image contains about 150 minutiaeâs. When we compare two fingerprint images, we compare latent and non latent fingerprint and we try to find 12 minutiaeâs placed on the same position on latent and non latent fingerprint images.
After fingerprint image pre-processing we can perform classification or we can try to find minutiae. In this paper we describe the process of minutiae classification for comparison purposes. For that purpose we use Walsh function and Walsh transforms. Paper describes minutiae classification which is relatively new in recognition systems and gives contribution for development of practical fingerprint recognition systems. Paper also gives contribution in the theoretical part due to the fact that Walsh functions were not implemented in fingerprint pre-processing systems so far. The new symbolic database model for fingerprint storage gives multifunctional foundations for future research
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