Publications

MToS: A tree of shapes for multivariate images

By Edwin Carlinet, Thierry Géraud

2015-10-26

In IEEE Transactions on Image Processing

Abstract

The Tree of Shapes (ToS) is a morphological tree that provides an high-level hierarchical representation of the image suitable for many image processing tasks. When dealing with color images, one cannot use the ToS because its definition is ill-formed on multivariate data. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems (color artifacts, loss of invariances…) In this paper, we highlight the need for a self-dual and contrast invariant representation of the image and provide a method that builds a single ToS by merging the shapes computed marginally and preserving the most important properties of the ToS. This method does not try to impose an arbitrary total ordering on values but uses only the inclusion relationship between shapes and the merging strategy works in a shape space. Eventually, we show the relevance of our method and our structure through several applications involving color and multispectral image analysis.

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Variations on parallel explicit model checking for generalized Büchi automata

By Étienne Renault, Alexandre Duret-Lutz, Fabrice Kordon, Denis Poitrenaud

2015-10-26

In International Journal on Software Tools for Technology Transfer (STTT)

Abstract

We present new parallel explicit emptiness checks for LTL model checking. Unlike existing parallel emptiness checks, these are based on a Strongly Connected Component (SCC) enumeration, support generalized Büchi acceptance, and require no synchronization points nor recomputing procedures. A salient feature of our algorithms is the use of a global union-find data structure in which multiple threads share structural information about the automaton checked. Besides these basic algorithms, we present one architectural variant isolating threads that write to the union-find, and one extension that decomposes the automaton based on the strength of its SCCs to use more optimized emptiness checks. The results from an extensive experimentation of our algorithms and their variations show encouraging performances, especially when the decomposition technique is used.

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SAT-based minimization of deterministic $\omega$-automata

By Souheib Baarir, Alexandre Duret-Lutz

2015-09-01

In Proceedings of the 20th international conference on logic for programming, artificial intelligence, and reasoning (LPAR’15)

Abstract

We describe a tool that inputs a deterministic $\omega$-automaton with any acceptance condition, and synthesizes an equivalent $\omega$-automaton with another arbitrary acceptance condition and a given number of states, if such an automaton exists. This tool, that relies on a SAT-based encoding of the problem, can be used to provide minimal $\omega$-automata equivalent to given properties, for different acceptance conditions.

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Using histogram representation and earth mover’s distance as an evaluation tool for text detection

By Stefania Calarasanu, Jonathan Fabrizio, Séverine Dubuisson

2015-08-01

In Proceedings of the 13th IAPR international conference on document analysis and recognition (ICDAR)

Abstract

In the context of text detection evaluation, it is essential to use protocols that are capable of describing both the quality and the quantity aspects of detection results. In this paper we propose a novel visual representation and evaluation tool that captures the whole nature of a detector by using histograms. First, two histograms (coverage and accuracy) are generated to visualize the different characteristics of a detector. Secondly, we compare these two histograms to a so called optimal one to compute representative and comparable scores. To do so, we introduce the usage of the Earth Mover’s Distance as a reliable evaluation tool to estimate recall and precision scores. Results obtained on the ICDAR 2013 dataset show that this method intuitively characterizes the accuracy of a text detector and gives at a glance various useful characteristics of the analyzed algorithm.

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Morphological object picking based on the color tree of shapes

By Edwin Carlinet, Thierry Géraud

2015-06-29

In Proceedings of 5th international conference on image processing theory, tools and applications (IPTA’15)

Abstract

The Tree of Shapes is a self-dual and contrast invariant morphological tree that provides a high-level hierarchical representation of images, suitable for many image processing tasks. Despite its powerfulness and its simplicity, it is still under-exploited in pattern recognition and computer vision. In this paper, we show that both interactive and automatic image segmentation can be achieved with some simple tree processings. To that aim, we rely on the “Color Tree of Shapes”, recently defined. We propose a method for interactive segmentation that does not involve any statistical learning, yet yielding results that compete with state-of-the-art approaches. We further extend this algorithm to unsupervised segmentation and give some results. Although they are preliminary, they highlight the potential of such an approach that works in the shape space.

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Une approche morphologique de segmentation interactive avec l’arbre des formes couleur

By Edwin Carlinet, Thierry Géraud

2015-06-16

In Actes du 15e colloque GRETSI

Abstract

L’arbre des formes est un arbre morphologique à la fois auto-dual et invariant par changement de contraste. Il fournit une représentation haut-niveau de l’image, intéressante pour de nombreuses tâches de traitement d’images. Malgré son potentiel et sa simplicité, il reste largement sous-utilisé en reconnaissance des formes et vision par ordinateur. Dans cet article, nous présentons une méthode de segmentation interactive qui s’effectue simplement en manipulant cet arbre. Pour cela, nous nous appuierons sur une représentation récemment définie : l’Arbre des Formes Couleur . La méthode de segmentation interactive que nous proposons ne requiert aucun apprentissage statistique ; néanmoins elle obtient des résultats qui rivalisent avec ceux de l’état de l’art. Bien que préliminaires, les résultats obtenus mettent en avant le potentiel et l’intérêt des méthodes travaillant dans l’espace des formes.

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On refinement of Büchi automata for explicit model checking

By František Blahoudek, Alexandre Duret-Lutz, Vojtčech Rujbr, Jan Strejček

2015-06-15

In Proceedings of the 22th international SPIN symposium on model checking of software (SPIN’15)

Abstract

In explicit model checking, systems are typically described in an implicit and compact way. Some valid information about the system can be easily derived directly from this description, for example that some atomic propositions cannot be valid at the same time. The paper shows several ways to apply this information to improve the Büchi automaton built from an LTL specification. As a result, we get smaller automata with shorter edge labels that are easier to understand and, more importantly, for which the explicit model checking process performs better.

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Practical stutter-invariance checks for $\omega$-regular languages

By Thibaud Michaud, Alexandre Duret-Lutz

2015-06-15

In Proceedings of the 22th international SPIN symposium on model checking of software (SPIN’15)

Abstract

We propose several automata-based constructions that check whether a specification is stutter-invariant. These constructions assume that a specification and its negation can be translated into Büchi automata, but aside from that, they are independent of the specification formalism. These transformations were inspired by a construction due to Holzmann and Kupferman, but that we broke down into two operations that can have different realizations, and that can be combined in different ways. As it turns out, implementing only one of these operations is needed to obtain a functional stutter-invariant check. Finally we have implemented these techniques in a tool so that users can easily check whether an LTL or PSL formula is stutter-invariant.

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Connected filtering on tree-based shape-spaces

By Yongchao Xu, Thierry Géraud, Laurent Najman

2015-06-05

In IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

Connected filters are well-known for their good contour preservation property. A popular implementation strategy relies on tree-based image representations: for example, one can compute an attribute characterizing the connected component represented by each node of the tree and keep only the nodes for which the attribute is sufficiently high. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is performed not in the space of the image, but in the space of shapes built from the image. Such a processing of shape-space filtering is a generalization of the existing tree-based connected operators. Indeed, the framework includes the classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on non-increasing attributes. Finally, we also propose a new class of connected operators that we call morphological shapings. Some illustrations and quantitative evaluations demonstrate the usefulness and robustness of the proposed shape-space filters.

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Combining explicit and symbolic LTL model checking using generalized testing automata

By Ala Eddine Ben Salem, Mohamed Graiet

2015-05-19

In Proceedings of the 15th international conference on application of concurrency to system design (ACSD’15)

Abstract

In automata-theoretic model checking, there are mainly two approaches: explicit and symbolic. In the explicit approach, the state-space is constructed explicitly and lazily during exploration (i.e., on-the-fly). The symbolic approach tries to overcome the state-space explosion obstacle by symbolically encoding the state-space in a concise way using decision diagrams. However, this symbolic construction is not performed on-the-fly as in the explicit approach. In order to take advantage of the best of both worlds, hybrid approaches are proposed as combinations of explicit and symbolic approaches. A hybrid approach is usually based on an on-the-fly construction of an explicit graph of symbolic nodes, where each symbolic node encodes a subset of states by means of binary decision diagrams. An alternative to the standard Büchi automata, called Testing automata have never been used before for hybrid model checking. In addition, in previous work, we have shown that Generalized Testing Automata (TGTA) can outperform the Büchi automata for explicit and symbolic model checking of stutter-invariant LTL properties. In this work, we investigate the use of these TGTA to improve hybrid model checking. We show how traditional hybrid approaches based on Generalized Büchi Automata (TGBA) can be adapted to obtain TGTA-based hybrid approaches. Then, each original approach is experimentally compared against its TGTA variant. The results show that these new variants are statistically more efficient.

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