131 research outputs found
An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test
Maintaining the attendance database of thousands of students has become a tedious task in the universities in Sri Lanka This paper comprises of 3 phases signature extraction signature recognition and signature verification to automate the process We applied necessary image processing techniques and extracted useful features from each signature Support Vector Machine SVM multiclass Support Vector Machine and Kolmogorov Smirnov test is used to signature classification recognition and verification respectively The described method in this report represents an effective and accurate approach to automatic signature recognition and verification It is capable of matching classifying and verifying the test signatures with the database of 83 33 100 and 100 accuracy respectivel
Biometrics & [and] Security:Combining Fingerprints, Smart Cards and Cryptography
Since the beginning of this brand new century, and especially since the 2001 Sept 11 events in the U.S, several biometric technologies are considered mature enough to be a new tool for security. Generally associated to a personal device for privacy protection, biometric references are stored in secured electronic devices such as smart cards, and systems are using cryptographic tools to communicate with the smart card and securely exchange biometric data. After a general introduction about biometrics, smart cards and cryptography, a second part will introduce our work with fake finger attacks on fingerprint sensors and tests done with different materials. The third part will present our approach for a lightweight fingerprint recognition algorithm for smart cards. The fourth part will detail security protocols used in different applications such as Personal Identity Verification cards. We will discuss our implementation such as the one we developed for the NIST to be used in PIV smart cards. Finally, a fifth part will address Cryptography-Biometrics interaction. We will highlight the antagonism between Cryptography – determinism, stable data – and Biometrics – statistical, error-prone –. Then we will present our application of challenge-response protocol to biometric data for easing the fingerprint recognition process
The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia
Conference Foreword
The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference
An offline writer independent signature verification method with robustness against scalings and rotations
Handwritten signatures are still one of the most used and accepted methods for user au thentication. They are used in a wide range of human daily tasks, including applications from banking to legal processes. The signature verification problem consists of verifying whether a given handwritten signature was generated by a particular person, by com paring it (directly or indirectly) to genuine signatures from that person. In this research work, a new offline writer-independent signature verification method is introduced (named VerSig-R), based on a combination of handcrafted Moving Least-Squares features and features transferred from a convolutional neural network. In our experiments, VerSig-R outperforms state-of-the-art techniques on Western-style signatures (CEDAR dataset), while also obtaining competitive results on South Asian-style handwriting (Bangla and Hindi datasets). Furthermore, a wide range of experiments demonstrate that VerSig-R is the most robust in relation to differences in scale and rotation of the signature images. This work also presents a discussion on dataset bias and on cross-dataset performance of VerSig-R, as well as a small user study showing that the proposed technique outperforms the expected human accuracy on the signature-verification task. Finally, a discussion on the impact of the number of signature examples (per writer) used during training on performance and execution time is presented
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Creating a virtual slide map from sputum smear images for region-of-interest localisation in automated microscopy
Includes abstract.Includes bibliographical references (leaves 140-144).Automated microscopy for the detection of tuberculosis (TB) in sputum smears seeks to address the strain on technicians in busy TB laboratories and to achieve faster diagnosis in countries with a heavy TB burden. As a step in the development of an automated microscope, the project described here was concerned with microscope auto-positioning; this primarily involves generating a point of reference on a slide, which can be used to automatically bring desired fields on the slide to the field-of-view of the microscope for re-examination. The study was carried out using a conventional microscope and Ziehl- Neelsen (ZN) stained sputum smear slides. All images were captured at 40x magnification. A digital replication, the virtual slide map, of an actual slide was constructed by combining the manually acquired images of the different fields of the slide. The geometric hashing scheme was found to be suitable for auto-stitching a large number of images (over 300 images) to form a virtual slide map. An object recognition algorithm, which was also based on the geometric hashing technique, was used to localise a query image (the current field-of-view) on the virtual slide map. This localised field-of-view then served as the point of reference. The true positive (correct localisation of a query image on the virtual slide map) rate achieved by the algorithm was above 88% even for noisy query images captured at slide orientations up to 26°. The image registration error, computed as the average mean square error, was less than 14 pixel2 (corresponding to 1.02 μm2 and 0.001% error in an image measuring 1030 x 1300 pixels) corresponding to a root mean square registration error of 3.7 pixels. Superior image registration accuracy was obtained at the expense of time using the scale invariant feature transform (SIFT), with a image registration error of 1 pixel2 (0.07 μm2). The object recognition algorithm is inherently robust to changes in slide orientation and placement, which are likely to occur in practice as it is impossible to place the slide in exactly the same position on the microscope at different times. Moreover, the algorithm showed high tolerance to illumination changes and robustness to noise
The synthesis of estuarine bathymetry from sparse sounding data
The two aims of the project involved:
1. Devising a system for prediction o f areas of bathymetric change within the Fal
estuary
2. Formulating and evaluating a method for interpolating single beam acoustic
bathymetry to avoid artefacts o f interpolation.
In order to address these aims, sources of bathymetric data for the Fal estuary were
identified as Truro Harbour Office, Cornwall County Council and the Environment
Agency. The data collected from these sources included red wavelength Lidar, aerial
photography and single beam acoustic bathymetry from a number of different years.
These data were input into a Geographic Information System (GIS) and assessed for
suitability for the purposes o f data comparison and hence assessment of temporal
trends in bathymetry within the estuary
Problems encountered during mterpolation of the acoustic bathymetry resulted in the
later aim of the project, to formulate an interpolation system suitable for interpolation
of the single beam, bathymetric data in a realistic way, avoiding serious artefacts of
interpolation. This aim was met, successfully, through the following processes:
1. An interpolation system was developed, using polygonal zones, bounded by
channels and coastlines, to prevent interpolation across these boundaries. This
system, based on Inverse Distance Weighting (IDW) interpolation, was referred to
as Zoned Inverse Distance Weighting (ZIDW).
2. ZIDW was found, by visual inspection, to eliminate the interpolation artefacts
described above.
3. The processes of identification of sounding lines and charmels, and the allocation
of soundings and output grid cells to polygons, were successfully automated to
allow ZIDW to be applied to large and multiple data sets. Manual intervention
was maintained for processes performed most successfully by the human brain to
optimise the results o f ZIDW.
4. To formalise the theory of ZIDW it was applied to a range of idealised,
mathematically defined chaimels. For simple straight and regular curved,
mathematical channels interpolation by the standard TIN method was found to
perform as well as ZIDW.
5. Investigation of sinusoidal channels within a rectangular estuary, however,
revealed that the TIN method begins to produce serious interpolation artefacts
where sounding lines are not parallel to the centre lines o f channels and ridges.
Hence, overall ZIDW was determined mathematically to represent the optimum
method o f interpolation for single beam, bathymelric data.
6. Finally, ZIDW was refined, using data from the Humber and Gironde estuaries, to
achieve universal applicability for interpolation of single beam, echo soimding
data from any estuary.
7. The refinements involved allowance for non-continuous, flood and ebb type
charmels; consideration of the effects of the scale of the estuary; smoothing of the
channels using cubic splines; interpolation using a 'smart' ellipse and the option to
reconstruct sounding lines from data that had previously been re-ordered
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