3D noisy discrete objects: Segmentation and application to smoothing

We propose in this paper a segmentation process that can deal with noisy discrete objects. A flexible approach considering arithmetic discrete planes with a variable width is used to avoid the over-segmentation that might happen when classical segmentation algorithms based on regular discrete planes are used to decompose the surface of the object. A method to choose a seed and different segmentation strategies according to the shape of the surface is also proposed, as well as an application to smooth the border of convex noisy discrete objects.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

Computing upper and lower bounds of rotation angles from digital images

Rotations in the discrete plane are important for many applications such as image matching or construction of mosaic images. We suppose that a digital image A is transformed to another digital image B by a rotation. In the discrete plane, there are many angles giving the rotation from A to B, which we call admissible rotation angles from A to B. For such a set of admissible rotation angles, there exist two angles that achieve the lower and the upper bounds. To find those lower and upper bounds, we use hinge angles as used in Nouvel and Rémila [Incremental and transitive discrete rotations, in: R. Reulke, U. Eckardt, B. Flash, U. Knauer, K. Polthier (Eds.), Combinatorial Image Analysis, Lecture Notes in Computer Science, vol. 4040, Springer, Berlin, 2006, pp. 199-213]. A sequence of hinge angles is a set of particular angles determined by a digital image in the sense that any angle between two consecutive hinge angles gives the identical rotation of the digital image. We propose a method for obtaining the lower and the upper bounds of admissible rotation angles using hinge angles from a given Euclidean angle or from a pair of corresponding digital images.     

Combining appearance and motion for face and gender recognition from videos

While many works consider moving faces only as collections of frames and apply still image-based methods, recent developments indicate that excellent results can be obtained using texture-based spatiotemporal representations for describing and analyzing faces in videos. Inspired by the psychophysical findings which state that facial movements can provide valuable information to face analysis, and also by our recent success in using LBP (local binary patterns) for combining appearance and motion for dynamic texture analysis, this paper investigates the combination of facial appearance (the shape of the face) and motion (the way a person is talking and moving his/her facial features) for face analysis in videos. We propose and study an approach for spatiotemporal face and gender recognition from videos using an extended set of volume LBP features and a boosting scheme. We experiment with several publicly available video face databases and consider different benchmark methods for comparison. Our extensive experimental analysis clearly assesses the promising performance of the LBP-based spatiotemporal representations for describing and analyzing faces in videos.     

Induction of multiclass multifeature split decision trees from distributed data

The decision tree-based classification is a popular approach for pattern recognition and data mining. Most decision tree induction methods assume training data being present at one central location. Given the growth in distributed databases at geographically dispersed locations, the methods for decision tree induction in distributed settings are gaining importance. This paper describes one such method that generates compact trees using multifeature splits in place of single feature split decision trees generated by most existing methods for distributed data. Our method is based on Fisher's linear discriminant function, and is capable of dealing with multiple classes in the data. For homogeneously distributed data, the decision trees produced by our method are identical to decision trees generated using Fisher's linear discriminant function with centrally stored data. For heterogeneously distributed data, a certain approximation is involved with a small change in performance with respect to the tree generated with centrally stored data. Experimental results for several well-known datasets are presented and compared with decision trees generated using Fisher's linear discriminant function with centrally stored data.     

Estimating the altitude of aerosol plumes over the ocean from reflectance ratio measurements in the O2 A-band

A methodology is proposed to infer the altitude of aerosol plumes over the ocean from reflectance ratio measurements in the O₂ absorption A-band (759 to 770 nm). The reflectance ratio is defined as the ratio of the reflectance in a first spectral band, strongly attenuated by O₂ absorption, and the reflectance in a second spectral band, minimally attenuated. For a given surface reflectance, simple relations are established between the reflectance ratio and the altitude of an aerosol layer, as a function of atmospheric conditions and the geometry of observation. The expected accuracy for various aerosol loadings and models is first quantified using an accurate, high spectral resolution, radiative transfer model that fully accounts for interactions between scattering and absorption. The method is developed for POLDER and MERIS, satellite sensors with adequate spectral characteristics. The simulations show that the method is only accurate over dark surfaces when aerosol optical thickness at 765 nm is relatively large (> 0.3). In this case, the expected accuracy is on the order of ± 0.5 km or ± 0.2 km for POLDER or MERIS respectively. More accurate estimates are obtained with MERIS, since in this case the spectral reflectance ratio is more sensitive to aerosol altitude. However, a precise spectral calibration is needed for MERIS. The methodology is applied to MERIS and POLDER imagery acquired over marine surfaces. The estimated aerosol altitude is compared with in situ lidar profiles of backscattering coefficient measured during the AOPEX-2004 experiment for MERIS, or obtained with the space-borne lidar CALIOP for POLDER. The retrieved altitudes agree with lidar measurements in a manner consistent with theory. These comparisons demonstrate the potential of the differential absorption methodology for obtaining information on aerosol altitude over dark surfaces.     

Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia

The impact of mineral aerosol (dust) in the Earth's system depends on particle characteristics which are initially determined by the terrestrial sources from which the sediments are entrained. Remote sensing is an established method for the detection and mapping of dust events, and has recently been used to identify dust source locations with varying degrees of success. This paper compares and evaluates five principal methods, using MODIS Level 1B and MODIS Level 2 aerosol data, to: (a) differentiate dust (mineral aerosol) from non-dust, and (2) determine the extent to which they enable the source of the dust to be discerned. The five MODIS L1B methods used here are: (1) un-processed false colour composite (FCC), (2) brightness temperature difference, (3) Ackerman's (1997: J.Geophys. Res., 102, 17069-17080) procedure, (4) Miller's (2003:Geophys. Res. Lett. 30, 20, art.no.2071) dust enhancement algorithm and (5) Roskovensky and Liou's (2005: Geophys. Res. Lett. 32, L12809) dust differentiation algorithm; the aerosol product is MODIS Deep Blue (Hsu et al., 2004: IEEE Trans. Geosci. Rem. Sensing, 42, 557-569), which is optimised for use over bright surfaces (i.e. deserts). These are applied to four significant dust events from the Lake Eyre Basin, Australia. OMI AI was also examined for each event to provide an independent assessment of dust presence and plume location. All of the techniques were successful in detecting dust when compared to FCCs, but the most effective technique for source determination varied from event to event depending on factors such as cloud cover, dust plume mineralogy and surface reflectance. Significantly, to optimise dust detection using the MODIS L1B approaches, the recommended dust/non-dust thresholds had to be considerably adjusted on an event by event basis. MODIS L2 aerosol data retrievals were also found to vary in quality significantly between events; being affected in particular by cloud masking difficulties. In general, we find that OMI AI and MODIS AQUA L1B and L2 data are complementary; the former are ideal for initial dust detection, the latter can be used to both identify plumes and sources at high spatial resolution. Overall, approaches using brightness temperature difference (BT10-11) are the most consistently reliable technique for dust source identification in the Lake Eyre Basin. One reason for this is that this enclosed basin contains multiple dust sources with contrasting geochemical signatures. In this instance, BTD data are not affected significantly by perturbations in dust mineralogy. However, the other algorithms tested (including MODIS Deep Blue) were all influenced by ground surface reflectance or dust mineralogy; making it impossible to use one single MODIS L1B or L2 data type for all events (or even for a single multiple-plume event). There is, however, considerable potential to exploit this anomaly, and to use dust detection algorithms to obtain information about dust mineralogy.     

Two efficient two-factor authenticated key exchange protocols in public wireless LANs

Recently, Parks et al. proposed an authentication and key agreement protocol for low-power PDAs in public wireless LANs using two factors including a password and a token, e.g. a smart card. They claimed that their proposed scheme provided mutual authentication, identity privacy, half-forward secrecy and low computation cost for a client including just one symmetric key encryption and five hash operations. In this paper, we point out that Park et al.’s protocol is vulnerable to the dictionary attack upon identity privacy. We propose two schemes with mutual authentication, half-forward secrecy, lower computation cost and less exchanged messages than Park et al.’s protocol. In additional to these properties, identity privacy, which is not satisfied by Park et al.’s protocol, is also provided by our second scheme.     

A routing-table-based adaptive and minimal routing scheme on network-on-chip architectures

In this paper, we present a routing algorithm that combines the shortest path routing and adaptive routing schemes for NoCs. In specific, routing follows the shortest path to ensure low latency and low energy consumption. This routing scheme requires routing information be stored in a series of routing tables created at the routers along the routing path from the source to the destination. To reduce the exploration space and timing cost for selecting the routing path, a routing list and routing table for each node are created off-line. Routing table is updated on-line to reflect the dynamic change of the network status to avoid network congestion. To alleviate the high hardware implementation cost associated with the routing tables, a method to help reduce the size of the routing tables is also introduced. Compared to the existing routing algorithms, the experimental results have confirmed that the proposed algorithm has better performance in terms of routing latency and power consumption.     

Parallel crypto-devices for GF(p) elliptic curve multiplication resistant against side channel attacks

All elliptic curve cryptographic schemes are based on scalar multiplication of points, and hence its faster computation signifies faster operation. This paper proposes two different parallelization techniques to speedup the GF(p) elliptic curve multiplication in affine coordinates and the corresponding architectures. The proposed implementations are capable of resisting different side channel attacks based on time and power analysis. The 160, 192, 224 and 256 bits implementations of both the architectures have been synthesized and simulated for both FPGA and 0.13μ CMOS ASIC. The final designs have been prototyped on a Xilinx Virtex-4 xc4vlx200-12ff1513 FPGA board and performance analyzes carried out. The experimental result and performance comparison show better throughput of the proposed implementations as compared to existing reported architectures.