Faculty of Information Technology

The prerequisite for the accurate iris recognition is to detect all iris occlusions which would otherwise confuse a recognition method and impair its recognition rate. This paper presents a fast multispectral eyelid, eyelash, and reflection detection method based on the underlying threedimensional spatial probabilistic textural model. The model first adaptively learns its parameters on the flawless iris texture part and subsequently checks for non iris occlusions using the recursive prediction analysis. We provide colour iris occlusion detection results that indicate the advantages of the proposed method and compare it with 97 recent Noisy Iris Challenge Evaluation algorithms.

In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We use this dense data as a reference for performance evaluation of the proposed BRDF sparse angular sampling and interpolation approach. The method is based on sampling of BRDF subspaces at fixed elevations by means of several adaptively-represented, uniformly distributed, perpendicular slices. Although this proposed method requires only a sparse sampling of material, the interpolation provides a very accurate reconstruction, visually and computationally comparable to densely measured reference. Due to the simple slices measurement and method's robustness it allows for a highly accurate acquisition of BRDFs. This in comparison with standard uniform angular sampling, is considerably faster yet uses far less samples.

A photo-realistic representation of material appearance can be achieved by means of bidirectional texture function (BTF) capturing a material's appearance for varying illumination, viewing directions, and spatial pixel coordinates. BTF captures many non-local effects in material structure such as inter-reflections, occlusions, shadowing, or scattering. The acquisition of BTF data is usually time and resource-intensive due to the high dimensionality of BTF data. This results in expensive, complex measurement setups and/or excessively long measurement times. We propose an approximate BTF acquisition setup based on a simple, affordable mechanical gantry containing a consumer camera and two LED lights. It captures a very limited subset of material surface images by shooting several video sequences. A psychophysical study comparing captured and reconstructed data with the reference BTFs of seven tested materials revealed that results of our method show a promising visual quality. Spe...

This paper presents a fast precise unsupervised iris defects detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding applied to demanding high resolution mobile device measurements. The accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections using the recursive prediction analysis. The method is developed for color eye images from unconstrained mobile devices but it was also successfully tested on the UBIRIS v2 eye database. Our method ranked first from the 97+1 recent Noisy Iris Challenge Evaluation contest alternative methods on this large color iris database using the exact contest data and methodology.

A photo-realistic representation of material appearance can be achieved by means of bidirectional texture function (BTF) capturing a material’s appearance for varying illumination, viewing directions, and spatial pixel coordinates. BTF captures many non-local effects in material structure such as inter-reflections, occlusions, shadowing, or scattering. The acquisition of BTF data is usually time and resource-intensive due to the high dimensionality of BTF data. This results in expensive, complex measurement setups and/or excessively long measurement times. We propose an approximate BTF acquisition setup based on a simple, affordable mechanical gantry containing a consumer camera and two LED lights. It captures a very limited subset of material surface images by shooting several video sequences. A psychophysical study comparing captured and reconstructed data with the reference BTFs of seven tested materials revealed that results of our method show a promising visual quality. As it a...

Accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. Undected iris occlusions otherwise dramatically decrease the iris recognition rate. This paper presents a fast multispectral iris occlusions detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections, eyelashes, and eyelids using the recursive prediction analysis. Our method obtains better accuracy with respect to the previously performed Noisy Iris Challenge Evaluation contest. It ranked first from the 97+2 alternative methods on this large colour iris database.

One of the most accurate yet still practical representation of material appearance is the Bidirectional Texture Function (BTF). The BTF can be viewed as an extension of Bidirectional Reflectance Distribution Function (BRDF) for additional spatial information that includes local visual effects such as shadowing, interreflection, subsurface-scattering, etc. However, the shift from BRDF to BTF represents not only a huge leap in respect to the realism of material reproduction, but also related high memory and computational costs stemming from the storage and processing of massive BTF data. In this work, we argue that each opaque material, regardless of its surface structure, can be safely substituted by a BRDF without the introduction of a significant perceptual error when viewed from an appropriate distance. Therefore, we ran a set of psychophysical studies over 25 materials to determine so-called critical viewing distances, i.e. the minimal distances at which the material spatial structure (texture) cannot be visually discerned. Our analysis determined such typical distances typical for several material categories often used in interior design applications. Furthermore, we propose a combination of computational features that can predict such distances without the need for a psychophysical study. We show that our work can significantly reduce rendering costs in applications that process complex virtual scenes.

Testing of digital circuits seems to be a completely mastered part of the design flow, but constrained test patterns generation is still a highly evolving branch of digital circuit testing. Our previous research on constrained test pattern generation proved that we can benefit from an implicit representation of test patterns set in CNF (Conjunctive Normal Form). Some techniques of speeding up the constrained SATbased test patterns generation are described and closely analyzed in this paper. These techniques are experimentally evaluated on a real SAT-based algorithm performing a constrained test patterns compression based on overlapping of test patterns. Experiments are performed on a subset of ISCAS'85 and '89 benchmark circuits. Results of the experiments are discussed and recommendations for a further development of similar SAT-based tools for constrained test patterns generation are given.

We present a method of improving the iterative power of resynthesis of Boolean networks in this paper. In principle it is based on iterative resynthesis of parts of the network, instead of processing the network as a whole. The parts are randomly selected, thus more variability is introduced. The process is scalable, at least as much as the state-of-the-art. We show that our method performs better than the academic state-of-the-art, the ABC tool from Berkeley. This is documented by extensive experiments on LGSynth'93 benchmark circuits.

In this paper we propose a new method of test patterns compression based on a design of a dedicated SAT-based ATPG (Automatic Test Pattern Generator). This compression method is targeted to systems on chip (SoCs) provided with the P1500 test standard. The RESPIN architecture can be used for test patterns decompression. The main idea is based on finding the best overlap of test patterns during the test generation, unlike other methods, which are based on efficient overlapping of pre-generated test patterns. The proposed algorithm takes advantage of an implicit test representation as SAT problem instances. The results of test patterns compression obtained for standard ISCAS'85 and '89 benchmark circuits are shown and compared with competitive test compression methods.

The analysis of Rule 90 CA by Martin, Odlyzko and Wolfram using diploynomials over finite fields is extended to Rule 60 CA with odd cylinder size. Two classes of such CA are recognized. Their maximum attractor lengths and transients characteristics are given. The basic building block, from which the entire state space can be produced, is identified for each type. An application of the results for diagnostic purpose is outlined.

Most of presently used academic logic synthesis tools, including SIS and ABC, are fully deterministic. Up to the knowledge of the authors, this holds for all available commercial tools as well. This means that no random decisions are made; the algorithms fully rely on deterministic heuristics. In this paper we present several hints of insufficiency of such an approach and show examples of perspective randomized logic synthesis algorithms. Judging from our experiments, these algorithms have a higher potential of performing better than the deterministic ones. Further we study how much randomness is actually needed for the algorithms to perform well. We show that some algorithms require only a small amount of randomness, while still taking full advantage of their randomized nature. On the other hand, some algorithms require a very high level of randomness to perform well. We propose reasons for this behavior and show a way of computing the necessary measure of randomness required.

Most of presently used academic logic synthesis tools, including SIS and ABC, are fully deterministic. Up to the knowledge of the authors, this holds for all available commercial tools as well. This means that no random decisions are made; the algorithms fully rely on deterministic heuristics. In this paper we present several hints of insufficiency of such an approach and show examples of perspective randomized logic synthesis algorithms. Judging from our experiments, these algorithms have a higher potential of performing better than the deterministic ones. Further we study how much randomness is actually needed for the algorithms to perform well. We show that some algorithms require only a small amount of randomness, while still taking full advantage of their randomized nature. On the other hand, some algorithms require a very high level of randomness to perform well. We propose reasons for this behavior and show a way of computing the necessary measure of randomness required. Keyw...

Recently, it has been shown that synthesis of some circuits is quite difficult for conventional methods. In this paper we present a method of minimization of multi-level logic networks which can solve these difficult circuit instances. The synthesis problem is transformed on the search problem. A search algorithm called Cartesian genetic programming (CGP) is applied to synthesize various difficult circuits. Conventional circuit synthesis usually fails for these difficult circuits; specific synthesis processes must be employed to obtain satisfactory results. We have found that CGP is able to implicitly discover new efficient circuit structures. Thus, it is able to optimize circuits universally, regardless their structure. The circuit optimization by CGP has been found especially efficient when applied to circuits already optimized by a conventional synthesis. The total runtime is reduced, while the result quality is improved further more.

The paper compares FPGA implementation of scaled polynomial basis and normal basis arithmetic units in the context of cryptographic coprocessor performing operations on elliptic curve points with coordinates in GF (2m). The hardware uses GCD division in polynomial ...

The paper describes FPGA implementation of cryptographic coprocessor performing operations on elliptic curve points with coordinates in GF (2 m). Polynomial basis and normal basis arithmetic units are presented and compared. Hardware implementation of GCD inversion in polynomial basis is described. Where an optimal normal basis exists, the normal basis arithmetic performs better. The digit width of 6 is shown to give the best area/performance ratio for optimal normal basis arithmetic.

It is known that EDA tools produce results of different quality dependent on seemingly neutral details in the input. We bring further results in this direction, which show that the differences can impair any quantitative comparisons of the tools. To gain qualitative insight, we present a stochastic model of result quality based on Gaussian Mixtures. We show on three case studies how these models help to evaluate and improve EDA algorithms.

We present experiments with synthesis tools using examples which are currently believed to be very hard, namely the LEKU examples by Cong and Minkovich and parity examples of our construction. In both cases, we found a way to produce reasonable results with existing tools. We identify the abilities that are crucial for achieving such results, and also generalize them to avoid similar cases of poor performance in future tools.

This paper presents a novel ATPG and test compression algorithm based on Pseudo-Boolean (PBO) optimization. Similarly to SAT-based ATPGs, the test for each fault is represented implicitly as a PBO instance. The optimization process solves the problem of maximizing the number of unspecified values in the test. A novel don't care aware circuit-to-PBO conversion procedure is presented. The obtained unspecified values in the test are efficiently exploited in test compression. The produced compressed test sequence is suited for the RESPIN decompression architecture, thus for testing systems-on-chip. The presented experimental results show the efficiency and competitiveness of the proposed method.

Circuits which are designed to be dependable are evaluated after gate-level design. To demonstrate the influence of implementation technology on dependability parameters, we developed a simple method which transforms the evaluation problem into conceptual hardware and then to SAT instances. The method can accommodate any combinational fault model. The performed evaluation demonstrated that the dependability parameters of the implementations correlate to a significant degree.