A robust braille recognition system

Braille is the most effective means of written communication between visually-impaired and sighted people. This paper describes a new system that recognizes Braille characters in scanned Braille document pages. Unlike most other approaches, an inexpensive flatbed scanner is used and the system requires minimal interaction with the user. A unique feature of this system is the use of context at different levels (from the pre-processing of the image through to the post-processing of the recognition results) to enhance robustness and, consequently, recognition results. Braille dots composing characters are identified on both single and double-sided documents of average quality with over 99% accuracy, while Braille characters are also correctly recognised in over 99% of documents of average quality (in both single and double-sided documents)

Gene–disease relationship discovery based on model-driven data integration and database view definition

Motivation: Computational methods are widely used to discover gene–disease relationships hidden in vast masses of available genomic and post-genomic data. In most current methods, a similarity measure is calculated between gene annotations and known disease genes or disease descriptions. However, more explicit gene–disease relationships are required for better insights into the molecular bases of diseases, especially for complex multi-gene diseases

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

EVALUATION OF LOW-COST DEPTH SENSORS FOR OUTDOOR APPLICATIONS

Depth information is a key component that allows a computer to reproduce human vision in plenty of applications from manufacturing, to robotics and autonomous driving. The Microsoft Kinect has brought depth sensing to another level resulting in a large number of low cost, small form factor depth sensors. Although these sensors can efficiently produce data over a wide dynamic range of sensing applications and within different environments, most of them are rather suitable for indoor applications. Operating in outdoor areas is a challenge because of undesired illumination, usually strong sunlight or surface scattering, which degrades measurement accuracy. Therefore, after presenting the different working principle of existing depth cameras, our study aims to evaluate where two very recent sensors, the AD-FXTOF1-EBZ and the flexx2, stand towards the issue of outdoor environment. In particular, measurement tests will be performed on different types of materials subjected to various illumination in order to evaluate the potential accuracy of such sensors

a.SCatch: semantic structure for architectural floor plan retrieval

Architects’ daily routine involves working with drawings. They use either a pen or a computer to sketch out their ideas or to do a drawing to scale. We therefore propose the use of a sketch-based approach when using the floor plan repository for queries. This enables the user of the system to sketch a schematic abstraction of a floor plan and search for floor plans that are structurally similar. We also propose the use of a visual query language, and a semantic structure as put forward by Langenhan. An algorithm extracts the semantic structure sketched by the architect on DFKI’s Touch& Write table and compares the structure of the sketch with that of those from the floor plan repository. The a.SCatch system enables the user to access knowledge from past projects easily. Based on CBR strategies and shape detection technologies, a sketch-based retrieval gives access to a semantic floor plan repository. Furthermore, details of a prototypical application which allows semantic structure to be extracted from image data and put into the repository semi-automatically are provided

Ontology-guided data preparation for discovering genotype-phenotype relationships

International audienceComplexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic frame to data and because they benefit from the progress of semantic web technologies, bio-ontologies should be considered for playing a key role in the KDD process. In the frame of a case study relative to the search of genotype-phenotype relationships, we demonstrate the capability of bio-ontologies to guide data selection during the preparation step of the KDD process. We propose three scenarios to illustrate how domain knowledge can be taken into account in order to select or aggregate data to mine, and consequently how it can facilitate result interpretation at the end of the process

Detecting Junctions Using Properties of the Laplacian of Gaussian Detector

This paper describes a fast junction detection algorithm using the Laplacian of Gaussian detector. We propose a general junction model and analyze its behavior in scale space. This study shows two properties: the Laplacian of Gaussian is zero at any junction and it has one or several elliptic extrema that always lie inside the junction sectors. These extrema move in scale space on lines passing by the junction point. Using these properties, we build an accurate and efficient junction detector. Experimental results confirm, in practice, the efficiency and the reliability of this detector

Elimination des faux contours par séparation et propagation de seuil

Un opérateur Laplacien d'une Gaussienne engendre une classe de faux points de contour qui ne peut-être supprimée par les méthode classiques de seuillage. Nous proposons un algorithme d'élimination des faux contours en tenant compte de leurs différentes origines. Par ailleurs, en étudiant le comportement du contour dans un espace échelle, nous déduisons un algorithme d'élimination automatique des faux contours obtenus à différentes échelles