Jean-Marc Ogier

Symbol and character recognition: application to engineering drawings

Abstract. In this paper, we consider the general problem of technical document interpretation, as applied to the documents of the French Telephonic Operator, France Télécom. More precisely, we focus the content of this paper on the computation of a new set of features allowing the classification of multioriented and multiscaled patterns. This set of invariants is based on the Fourier–Mellin Transform. The interests of this computation rely on the excellent classification rate obtained with this method and also on using this Fourier–Mellin transform within a “filtering mode”, with which we can solve the well known difficult problem of connected character recognition.

Local structural analysis: A primer

The structural analysis is a processing step during which graphs are extracted from binary images. We can decompose the structural analysis into local and global approaches. The local approach decomposes the connected components, and the global approach groups them together. This paper deals especially with the local structural analysis. The local structural analysis is employed for different applications like symbol recognition, line drawing interpretation, and character recognition. We propose here a primer on the local structural analysis. First, we propose a general decomposition of the local structural analysis into four steps: object graph extraction, mathematical approximation, high-level object construction, and object graph correction. Then, we present some considerations on the method comparison and combination.

Knowledge Representation and Acquisition for Engineering Document Analysis

This paper tackles the problem of bootstrapping engineering documents recognition systems. A user-friendly interface is presented. Its aim is to acquire knowledge concerning the graphical appearance of objects, but also to learn the best approach to use among our tools in order to recognise the learned objects.

Combination of Invariant Pattern Recognition Primitives on Technical Documents

This paper deals with a particular aspect of a technical document interpretation device: the recognition of multi-oriented and multiscaled characters and symbols. The adopted methodology is based on original descriptors, relying on the computation of the Mellin Fourier Transform. These descriptors are then combined with classical invariant through the use of Genetic Algorithms. The application frame of this study is the interpretation of the documents of the French telephonic operator France-Telecom for which the recognition of symbols constitutes a crucial point for a robust interpretation.

Adaptable Vectorisation System Based on Strategic Knowledge and XML Representation Use

This paper presents a vectorisation system based on the use of strategic knowledge. This one is composed of two parts: a processing library and a graphic user interface. Our processing library is composed of image pre-processing and vectorisation tools. Our graphic user interface is used for the strategic knowledge acquisition and operationalisation. It allows to construct and to execute scenarios, exploiting any processing of our library, according to documents’ contexts and users’ adopted strategies. A XML data representation is used, allowing an easy data manipulation. A scenario example is presented for graphics recognition on utility maps.

A Topological Measure for Image Object Recognition

All the effective object recognition systems are based on a powerful shape descriptor. We propose a new method for extracting the topological feature of an object. By connecting all the pixels constituting the object under the constraint to define the shortest path (minimum spanning tree) we capture the shape topology. The tree length is in the first approximation the key of our object recognition system. This measure (with some adjustments) make it possible to detect the object target in several geometrical configurations (translation / rotation) and it seems to have many desirable properties such as discrimination power and robustness to noise, that is the conclusion of the preliminary tests on characters and symbols.

Multi-scaled and multi oriented character recognition: an original strategy

We propose an original methodology allowing detection and recognition of multi-oriented and multi-scaled shapes. The supports on which the method is applied are technical documents representing the network of the French telephonic operator (France Telecom) overlaid on urban maps. The adopted technique, based on the Mellin Fourier Transform is integrated in a global strategy that permits one to solve ambiguous situations, through the provision of contextual information. The strategy, which is applied to solve the character/symbol classification problem, can be divided into two stages. The first one consists of constructing a moment invariants vector from each shape which is extracted from a character layer issued from the system approach. The second consists of detecting and recognising connected shapes. The results of the application of this technique are very encouraging, since the classification rate reaches excellent scores if we consider that no contextual information has been integrated in the recognition process (orientation of the string, integration of data issued from dictionaries stored on alpha-numeric databases).

Graphic Recognition: The Concept Lattice Approach

Object recognition is a very large problem that can be derived in different forms. In the domain of graphic recognition, many strategies are proposed, but many of them depend on the context in which they are applied [LVSM01]. This aspect implies the necessity to find a model for this context, and to use it for the implementation of dynamic and adaptative systems. In this paper, we focus on the object recognition problem where a knowledge base defined by a finite set of representative prototypes or class objects is given.

Processing of the Connected Shapes in Raster-to-Vector Conversion Process

We present in this paper a methodology dealing with raster to vector conversion for technical documents interpretation. The adopted approach considers the problem of information layer separation. The retained strategy consists in applying a sequence of different specialists the aim of which is to process a particular problem. Even if many commercial systems exist, this kind of problem constitutes a real difficulty which is not completely solved. The obtained results are evaluated and discussed in the context of French Telephonic Network Documents Interpretation.

Technical Map Interpretation: A Distributed Approach

Abstract:This paper deals with the general problem of document understanding. We propose the description of a formal architecture of a device capable of interpreting technical and cartographic documents. This device relies on two main points, i.e. a model of the document and the implementation of a set of ‘builders’, the aim of which is to progressively construct information of as high a semantic level as that provided by the document drawer. Two main stages are integrated in the reasoning process: the first one consists in constructing the information, through a bottom-up approach. Then, a cycling stage is triggered to solve ambiguities detected by the system and corresponding to inconsistent objects with regard to the document model. In this paper, the whole approach is presented in the context of the French cadaster interpretation. The first implementation has enabled us to quantify the interpretation results and to verify the relevance of the cycling stage.