Image normalization by complex moments

The role of moments in image normalization and invariant pattern recognition is addressed. The classical idea of the principal axes is analyzed and extended to a more general definition. The relationship between moment-based normalization, moment invariants, and circular harmonics is established. Invariance properties of moments, as opposed to their recognition properties, are identified using a new class of normalization procedures. The application of moment-based normalization in pattern recognition is demonstrated by experiment.     

Recognitive aspects of moment invariants

Moment invariants are evaluated as a feature space for pattern recognition in terms of discrimination power and noise tolerance. The notion of complex moments is introduced as a simple and straightforward way to derive moment invariants. Through this relation, properties of complex moments are used to characterize moment invariants. Aspects of information loss, suppression, and redundancy encountered in moment invariants are investigated and significant results are derived. The behavior of moment invariants in the presence of additive noise is also described.     

Holographic data storage

Research into and the development of data storage devices is a race to keep up with the continuing demand for more capacity, more density, and faster readout rates. Improvements in conventional memory technologies-magnetic hard disk drives, optical disks, and semiconductor memories-have managed to keep pace with the demand for bigger, faster memories. However, there is strong evidence that these two-dimensional surface storage technologies are approaching fundamental limits. An alternative approach for next-generation memories is to store data in three dimensions. This article describes developments in holographic 3D memories, in which high density is achieved by superimposing many holograms within the same volume of recording material. Holographic storage is a promising candidate for next-generation storage. Research has demonstrated that holographic storage systems with desirable properties can be engineered. The next step is to build these systems at costs competitive with those of existing technologies and to optimize the storage media     

Snakes: Active contour models

A snake is an energy-minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines and edges. Snakes are active contour models: they lock onto nearby edges, localizing them accurately. Scale-space continuation can be used to enlarge the capture region surrounding a feature. Snakes provide a unified account of a number of visual problems, including detection of edges, lines, and subjective contours; motion tracking; and stereo matching. We have used snakes successfully for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest.     

Thermal fixing of 10,000 Holograms in LiNbO3:Fe

We discuss thermal fixing as a solution to the volatility problem in holographic storage systems that use photorefractive materials such as LiNbO(3):Fe. We present a systematic study to characterize the effect of thermal fixing on the error performance of a large-scale holographic memory. We introduce a novel, to our knowledge, incremental fixing schedule to improve the overall system fixing efficiency. We thermally fixed 10,000 holograms in a 90 degrees -geometry setup by using this new schedule. All the fixed holograms were retrieved with no errors.     

Volume holographic hyperspectral imaging

A volume hologram has two degenerate Bragg-phase-matching dimensions and provides the capability of volume holographic imaging. We demonstrate two volume holographic imaging architectures and investigate their imaging resolution, aberration, and sensitivity. The first architecture uses the hologram directly as an objective imaging element where strong aberration is observed and confirmed by simulation. The second architecture uses an imaging lens and a transmission geometry hologram to achieve linear two-dimensional optical sectioning and imaging of a four-dimensional (spatial plus spectral dimensions) object hyperspace. Multiplexed holograms can achieve simultaneously three-dimensional imaging of an object without a scanning mechanism.     

Autonomous pedestrians

We address the challenging problem of emulating the rich complexity of real pedestrians in urban environments. Our artificial life approach integrates motor, perceptual, behavioral, and cognitive components within a comprehensive model of pedestrians as individuals. Featuring innovations in these components, as well as in their combination, our model yields results of unprecedented fidelity and complexity for fully autonomous multihuman simulation in a large urban environment. We represent the environment using hierarchical data structures, which efficiently support the perceptual queries that influence the behavioral responses of the autonomous pedestrians and sustain their ability to plan their actions on local and global scales.     

Linear and logarithmic capacities in associative neural networks

A model of associate memory incorporating global linearity and pointwise nonlinearities in a state space of n-dimensional binary vectors is considered. Attention is focused on the ability to store a prescribed set of state vectors as attractors within the model. Within the framework of such associative nets, a specific strategy for information storage that utilizes the spectrum of a linear operator is considered in some detail. Comparisons are made between this spectral strategy and a prior scheme that utilizes the sum of Kronecker outer products of the prescribed set of state vectors, which are to function nominally as memories. The storage capacity of the spectral strategy is linear in n (the dimension of the state space under consideration), whereas an asymptotic result of n/4 log n holds for the storage capacity of the outer product scheme. Computer-simulated results show that the spectral strategy stores information more efficiently. The preprocessing costs incurred in the two algorithms are estimated, and recursive strategies are developed for their computation