Watermarking for Multimedia Security using Complex Wavelets

This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms.

Partial Palmprint Matching Using Invariant Local Minutiae Descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment and minutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposed where the partial palmprint’s minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to each minutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained show that the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

The formal specification of abstract data types and their implementation in Fortran 90: Implementation issues concerning the use of pointers

In this paper we continue our investigation into the development of computational-science software based on the identification and formal specification of Abstract Data Types (ADTs) and their implementation in Fortran 90. In particular, we consider the consequences of using pointers when implementing a formally specified ADT in Fortran 90. Our aim is to highlight the resulting conflict between the goal of information hiding, which is central to the ADT methodology, and the space efficiency of the implementation. We show that the issue of storage recovery cannot be avoided by the ADT user, and present a range of implementations of a simple ADT to illustrate various approaches towards satisfactory storage management. Finally, we propose a set of guidelines for implementing ADTs using pointers in Fortran 90. These guidelines offer a way gracefully to provide disposal operations in Fortran 90. Such an approach is desirable since Fortran 90 does not provide automatic garbage collection which is offered by many object-oriented languages including Eiffel, Java, Smalltalk, and Simula.