Colour and rotation invariant textural features based on Markov random fields

A visual appearance of natural materials significantly depends on acquisition circumstances, particularly illumination conditions and viewpoint position, whose variations cause difficulties in the analysis of real scenes. We address this issue with novel texture features, based on fast estimates of Markovian statistics, that are simultaneously rotation and illumination invariant. The proposed features are invariant to in-plane material rotation and illumination spectrum (colour invariance), they are robust to local intensity changes (cast shadows) and illumination direction. No knowledge of illumination conditions is required and recognition is possible from a single training image per material. The material recognition is tested on the currently most realistic visual representation - Bidirectional Texture Function (BTF), using CUReT and ALOT texture datasets with more than 250 natural materials. Our proposed features significantly outperform leading alternatives including Local Binary Patterns (LBP, LBP-HF) and texton MR8 methods.     

Incremental Branching Programs

We propose a new model of restricted branching programs specific to solving GEN problems, which we call incremental branching programs. We show that syntactic incremental branching programs capture previously studied models of computation for the problem GEN, namely marking machines (Cook, S.A. in J. Comput. Syst. Sci. 9(3):308–316, 1974) and Poon’s extension (Proc. of the 34th IEEE Symp. on the Foundations of Computer Science, pp. 218–227, 1993) of jumping automata on graphs (Cook, S.A., Rackoff, C.W. in SIAM J. Comput. 9:636–652, 1980). We then prove exponential size lower bounds for our syntactic incremental model, and for some other variants of branching program computation for GEN. We further show that nondeterministic syntactic incremental branching programs are provably stronger than their deterministic counterpart when solving a natural NL-complete GEN sub-problem. It remains open if syntactic incremental branching programs are as powerful as unrestricted branching programs for GEN problems. A preliminary version of this paper appears as (Gál, A., Koucky, M., McKenzie, P., Incremental branching programs, in Proc. of the 2006 Computer Science in Russia Conference CSR06. Lecture Notes in Computer Science, vol. 3967, pp. 178–190, 2006). A. Gal supported in part by NSF Grant CCF-0430695 and an Alfred P. Sloan Research Fellowship. M. Koucky did part of this work while being a postdoctoral fellow at McGill University, Canada and at CWI, Amsterdam, Netherlands. Supported in part by NWO vici project 2004–2009, project No. 1M0021620808 of MŠMT ČR, grants 201/07/P276, 201/05/0124 of GA ČR, and Institutional Research Plan No. AV0Z10190503. P. McKenzie supported by the NSERC of Canada and the (Québec) FQRNT.     

Registration of challenging image pairs: initialization, estimation, and decision

Our goal is an automated 2D-image-pair registration algorithm capable of aligning images taken of a wide variety of natural and man-made scenes as well as many medical images. The algorithm should handle low overlap, substantial orientation and scale differences, large illumination variations, and physical changes in the scene. An important component of this is the ability to automatically reject pairs that have no overlap or have too many differences to be aligned well.We propose a complete algorithm, including techniques for initialization, for estimating transformation parameters, and for automatically deciding if an estimate is correct. Keypoints extracted and matched between images are used to generate initial similarity transform estimates, each accurate over a small region. These initial estimates are rank-ordered and tested individually in succession. Each estimate is refined using the Dual-Bootstrap ICP algorithm, driven by matching of multiscale features. A three-part decision criteria, combining measurements of alignment accuracy, stability in the estimate, and consistency in the constraints, determines whether the refined transformation estimate is accepted as correct. Experimental results on a data set of 22 challenging image pairs show that the algorithm effectively aligns 19 of the 22 pairs and rejects 99.8% of the misalignments that occur when all possible pairs are tried. The algorithm substantially out-performs algorithms based on keypoint matching alone.     

Combining classifiers under probabilistic models: experimental comparative analysis of methods

This work will present a review of the concept of classifier combination based on the combined discriminant function. We will present a Bayesian approach, in which the discriminant function assumes the role of the posterior probability. We will propose a probabilistic interpretation of expert rules and conditions of knowledge consistency for expert rules and learning sets. We will suggest how to measure the quality of learning materials and we will use the measure mentioned above for an algorithm that eliminates contradictions in the rule set. In this work several recognition algorithms will be described, based on either: (i) pure rules, or; (ii) rules together with learning sets. Furthermore, the original concept of information unification, which enables the formation of rules on the basis of learning set or learning set on the basis of rules will be proposed. The obtained conclusions will serve as a spring‐board for the formulation of new project guidelines for this type of decision‐making system. At the end, experimental results of the proposed algorithms will be presented, both from computer generated data and for a real problem from the medical diagnostics field.     

Image auto-annotation with automatic selection of the annotation length

Developing a satisfactory and effective method for auto-annotating images that works under general conditions is a challenging task. The advantages of such a system would be manifold: it can be used to annotate existing, large databases of images, rendering them accessible to text search engines; or it can be used as core for image retrieval based on a query image’s visual content. Manual annotation of images is a difficult, tedious and time consuming task. Furthermore, manual annotations tend to show great inter-person variance: considering an image, the opinions about what elements are significant and deserve an annotation vary strongly. The latter poses a problem for the evaluation of an automatic method, as an annotation’s correctness is greatly subjective. In this paper we present an automatic method for annotating images, which addresses one of the existing methods’ major limitation, namely a fixed annotation length. The proposed method, PATSI, automatically chooses the resulting annotation’s length for each query image. It is held as simple as possible and a build-in parameter optimization procedure renders PATSI de-facto parameter free. Finally, PATSI is evaluated on standard datasets, outperforming various state-of-the-art methods.     

Surface hardening of Ti alloys by gas-phase nitridation: Kinetic control of the nitrogen surface activity

A new concept for surface hardening of titanium alloys has been developed and successfully applied to Ti-6Al-4V alloys: gas-phase nitridation under kinetic control of the nitrogen activity. This method avoids the formation of detrimental second-phase nitrides by nitriding under a very low nitrogen activity, combined with rapid diffusion of nitrogen into the specimen. The surface hardness of the Ti-6Al-4V alloy was increased by a factor of 2 to ≈ 12 GPa, with only modest attenuation of ductility. We have realized conditions for generating case depths of ≈ 25 μm in reasonable nitridation times. The nitrogen activity in the gas phase is generated by heating a powder pack of Cr and Cr₂N. A closed two-zone system allows the powder pack and the specimen to be at different temperatures, optimizing both the nitrogen partial pressure and the nitrogen diffusion into the specimen. This low-cost, conformal nitridation process generates a smoothly graded nitrogen concentration profile and can be applied to finished Ti alloy components.     

Alzheimer paired helical filaments (PHFs) studied by high-resolution TEM: what can vertical Pt-C replication tell us about the organization of the pronase-digested PHF core?

Untreated paired helical filaments (PHFs) and pronase-digested PHF-core filaments were stereoscopically imaged with a freeze-drying vertical platinum-carbon replication preparation method for TEM. The untreated PHF have an average wide region (W) = 22.8 +/- 2.4 nm, a narrow region (T) = 10.6 +/- 1.7 nm, and a helical turn period (L) = 78.6 +/- 13.4. The surfaces of the untreated PHF's fuzzy coat appears disorganized. The widths of the pronase-treated PHF-core filaments were significantly reduced (W(d) = 14.8 +/- 1.2 nm, T(d) = 5.7 +/- 1.0 nm, and L(d) = 75.4 +/- 17 nm). The surfaces of the untreated PHF contained approximately 1.1 nm strands, the same size as tau monomer ( approximately 1.0 nm). The pronase-digested PHF cores mostly contained approximately 1.6 +/- 0.3 nm strands although strand diameters ranged from 0.6-2.5 nm. The strands sometimes appear to be wrapped around the filament axis; less often, they appear to be roughly parallel to the PHF axis, and otherwise appear to be randomly oriented. Images of pronase-digested PHF core images are discussed in relation to the core's biochemical composition, its proposed beta structure, and structural subunit models. Images of the untreated and the pronase-digested PHF support a helical ribbon morphology.     

DNA-directed immobilization of horseradish peroxidase onto porous SiO2optical transducers

ABSTRACT: Multifunctional porous Si nanostructure is designed to optically monitor enzymatic activity of Horseradish Peroxidase. First, an oxidized PSi optical nanostructure, a Fabry-Perot thin film, is synthesized and is used as the optical transducer element. Immobilization of the enzyme onto the nanostructure is performed through DNA-Directed Immobilization. Preliminary studies demonstrate high enzymatic activity levels of the immobilized Horseradish Peroxidase, while maintaining its specificity. The catalytic activity of the enzymes immobilized within the porous nanostructure is monitored in real time by reflective interferometric Fourier transform spectroscopy. We show that we can easily regenerate the surface for consecutive biosensing analysis by mild de-hybridization conditions.