L’Arbre des Formes (ToS) est un arbre morphologique qui fournit une représentation hiérarchique de l’image auto-duale et invariante par changement de contraste. De ce fait, il est adapté à de nombreuses applications de traitement d’images. Néanmoins, on se heurte à des problèmes avec l’Arbre des Formes lorsqu’on doit traiter des images couleurs car sa définition tient uniquement en niveaux de gris. Les solutions les plus courantes sont alors d’effectuer un traitement composante par composante (marginal) ou d’imposer un ordre total. Ces solutions ne sont généralement pas satisfaisantes et font survenir des problèmes (des artefacts de couleur, des pertes de propriétés...) Dans cet article, nous insistons sur la nécessité d’une représentation à la fois auto-duale et invariante par changement de contraste et nous proposons une méthode qui construit un Arbre des Formes unique en fusionnant des formes issues des composantes marginales tout en préservant les propriétés intrinsèques de l’arbre. Cette méthode s’affranchit de tout relation d’ordre totale en utilisant uniquement la relation d’inclusion entre les formes et en effectuant une fusion dans l’espace des formes. Finalement, nous montrerons la pertinence de notre méthode et de la structure en les illustrant sur de la simplification d’images et de la segmentation interactive.

An important topic for the image processing and pattern recognition community is the construction of open source and efficient libraries. An increasing number of software frameworks are said to be generic: they allow users to write reusable algorithms compatible with many input image types. However, this design choice is often made at the expense of performance. We present an approach to preserve efficiency in a generic image processing framework, by leveraging data types features. Variants of generic algorithms taking advantage of image types properties can be defined, offering an adjustable trade-off between genericity and efficiency. Our experiments show that these generic optimizations can match dedicated code in terms of execution times, and even sometimes perform better than routines optimized by hand. Digital Topology software should reflect the generality of the underlying mathematics: mapping the latter to the former requires genericity. By designing generic solutions, one can effectively reuse digital topology data structures and algorithms. We propose an image processing framework focused on the Generic Programming paradigm in which an algorithm on the paper can be turned into a single code, written once and usable with various input types. This approach enables users to design and implement new methods at a lower cost, try cross-domain experiments and help generalize results.

The Tree of Shapes is a morphological tree that provides an high-level hierarchical representation of the image suitable for many image processing tasks. This structure has the desirable properties to be self-dual and contrast-invariant and describes the organization of the objects through level lines inclusion. Yet it is defined on gray-level while many images have multivariate data (color images, multispectral images…) where information are split across channels. In this paper, we propose some leads to extend the tree of shapes on colors with classical approaches based on total orders, more recent approaches based on graphs and also a new distance-based method. Eventually, we compare these approaches through denoising to highlight their strengths and weaknesses and show the strong potential of the new methods compared to classical ones.

The tree of shapes is a self-dual tree-based image representation belonging to the field of mathematical morphology. This representation is highly interesting since it is invariant to contrast changes and inversion, and allows for numerous and powerful applications. A new algorithm to compute the tree of shapes has been recently presented: it has a quasi-linear complexity; it is the only known algorithm that is also effective for nD images with n > 2; yet it is sequential. With the increasing size of data to process, the need of a parallel algorithm to compute that tree is of prime importance; in this paper, we present such an algorithm. We also give some benchmarks that show that the parallel version is computationally effective. As a consequence, that makes possible to process 3D images with some powerful self-dual morphological tools.

In this article, we propose a simple and precise skew estimation algorithm for binarized document images. The estimation is performed in the frequency domain. To get a precise result, the Fourier transform is not applied to the document itself but the document is preprocessed: all regions of the document are clustered using a KNN and contours of grouped regions are smoothed using the convex hull to form more regular shapes, with better orientation. No assumption has been made concerning the nature or the content of the document. This method has been shown to be very accurate and was ranked first at the DISEC’13 contest, during the ICDAR competitions.

Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. In this paper we present the method that has won in 2013 the staff removal competition, organized at the International Conference on Document Analysis and Recognition (ICDAR). The main characteristics of this method is that it essentially relies on mathematical morphology filtering. So it is simple, fast, and its full source code is provided to favor reproducible research.

Many methods based on the morphological notion of <i>shapes</i> (<i>i.e.</i>, connected components of level sets) have been proved to be very efficient in shape recognition and shape analysis. The inclusion relationship of the level lines (boundaries of level sets) forms the tree of shapes, a tree-based image representation with a high potential. Numerous applications using this tree representation have been proposed. In this article, we propose an efficient algorithm that extracts a set of disjoint level lines in the image. These selected level lines yields a simplified image with clean contours, which also provides an intuitive idea about the main structure of the tree of shapes. Besides, we obtain a saliency map without transition problems around the contours by weighting level lines with their significance. Experimental results demonstrate the efficiency and usefulness of our method.

Software systems have become ubiquitous in our everyday life. They replace humans for critical tasks that involve high costs and even human lives. The serious consequences caused by the failure of such systems make crucial the use of rigorous methods for system validation. One of the widely-used formal verification methods is the automata-theoretic approach to model checking. It takes as input a model of the system and a property, and answers if the model satisfies or not the property. To achieve this goal, it translates the negation of the property in an automaton and checks whether the product of the model and this automaton is empty. Although it is automatic, this approach suffers from the combinatorial explosion of the resulting product. To tackle this problem, especially when checking stutter-invariant LTL properties, we firstly improve the two-pass verification algorithm of Testing automata (TA), then we propose a transformation of TA into a normal form (STA) that only requires a single-pass verification algorithm. We also propose a new type of automata: the TGTA. These automata also enable a check in a single-pass and without adding artificial states : it combines the benefits of TA and generalized Büchi automata (TGBA). TGTA improve the explicit and symbolic model checking approaches. In particular, by combining TGTA with the saturation technique, the performances of the symbolic approach has been improved by an order of magnitude compared to TGBA. Used in hybrid approaches TGTA prove complementary to TGBA. All the contributions of this work have been implemented in SPOT and LTS-ITS, respectively, an explicit and a symbolic open source model-checking libraries.

Natural and synthetic discrete images are generally not well-composed, leading to many topological issues: connectivities in binary images are not equivalent, the Jordan Separation theorem is not true anymore, and so on. Conversely, making images well-composed solves those problems and then gives access to many powerful tools already known in mathematical morphology as the Tree of Shapes which is of our principal interest. In this paper, we present two main results: a characterization of 3D well-composed gray-valued images; and a counter-example showing that no local self-dual interpolation with a classical set of properties makes well-composed images with one subdivision in 3D, as soon as we choose the mean operator to interpolate in 1D. Then, we briefly discuss various constraints that could be interesting to change to make the problem solvable in nD.

Connected operators are morphological tools that have the property of filtering images without creating new contours and without moving the contours that are preserved. Those operators are related to the max-tree and min-tree repre- sentations of images, and many algorithms have been proposed to compute those trees. However, no exhaustive comparison of these algorithms has been proposed so far, and the choice of an algorithm over another depends on many parameters. Since the need for fast algorithms is obvious for production code, we present an in-depth comparison of the existing algorithms in a unique framework, as well as variations of some of them that improve their efficiency. This comparison involves both sequential and parallel algorithms, and execution times are given with respect to the number of threads, the input image size, and the pixel value quantization. Eventually, a decision tree is given to help the user choose the most appropriate algorithm with respect to the user requirements. To favor reproducible research, an online demo allows the user to upload an image and bench the different algorithms, and the source code of every algorithms has been made available.