International Journal of Pattern Recognition and Artificial Intelligence, 2014
In this paper, we address a new scheme for symbol retrieval based on bag-of-relations (BoRs) whic... more In this paper, we address a new scheme for symbol retrieval based on bag-of-relations (BoRs) which are computed between extracted visual primitives (e.g. circle and corner). Our features consist of pairwise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological relation information indexed in bags-of-relations and use this for recognition. As a consequence, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using several different well known datasets such as GREC, FRESH and SESYD, and includes a comparison with state-of-the-art descriptors. Experiments provide interesting results on symbol spotting and other user-friendly symbol retrieval applications.
International Journal of Pattern Recognition and Artificial Intelligence, 2013
In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the... more In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalisation based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behaviour by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.
2013 12th International Conference on Document Analysis and Recognition, 2013
In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BO... more In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BOFs) which are computed between the extracted visual primitives. Our feature consists of pairwise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological information to guide directional relations. Consequently, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using two different datasets. Experimental tests provide interesting results by establishing user-friendly symbol retrieval application.
International Journal on Document Analysis and Recognition, 2013
This paper develops a structural symbol recognition method with integrated statistical features. ... more This paper develops a structural symbol recognition method with integrated statistical features. It applies spatial organization descriptors to the identified shape features within a fixed visual vocabulary that compose a symbol. It builds an attributed relational graph expressing the spatial relations between those visual vocabulary elements. In order to adapt the chosen vocabulary features to multiple and possible specialized contexts, we study the pertinence of unsupervised clustering to capture significant shape variations within a vocabulary class and thus refine the discriminative power of the method. This unsupervised clustering relies on cross-validation between several different cluster indices. The resulting approach is capable of determining part of the pertinent vocabulary and significantly increases recognition results with respect to the state-of-the-art. It is experimentally validated on complex electrical wiring diagram symbols.
Abstract. In this paper we present a way to use precision and recall measures in total absence of... more Abstract. In this paper we present a way to use precision and recall measures in total absence of ground truth. We develop a probabilistic interpretation of both measures and show that, provided a sufficient number of data sources are available, it offers a viable performance measure to compare methods if no ground truth is available. This paper also shows the limitations of the approach, in case a systematic bias is present in all compared methods, but shows that it maintains a very high level of overall coherence and stability.
In this paper, we present a method for symbol recognition based on the spatio-structural descript... more In this paper, we present a method for symbol recognition based on the spatio-structural description of a 'vocabulary'of extracted visual elementary parts. It is applied to symbols in electrical wiring diagrams. The method consists of first identifying vocabulary elements into different groups based on their types (eg, circle, corner). We then compute spatial relations between the possible pairs of labelled vocabulary types which are further used as a basis for building an attributed relational graph that fully describes the symbol.
Abstract. In this paper we summarize the framework and the results of the fourth edition of the I... more Abstract. In this paper we summarize the framework and the results of the fourth edition of the International Symbol Recognition Contest, organized in the context of GREC'11. The contest follows the series started at the GREC'03 workshop and it is the first time that, in addition to recognition of isolated symbols, the contest includes the evaluation of symbol spotting.
The Document Analysis and Exploitation platform is a sophisticated technical environment that con... more The Document Analysis and Exploitation platform is a sophisticated technical environment that consists of a repository containing document images, implementations of document analysis algorithms, and the results of these algorithms when applied to data in the repository. The use of a webservices model makes it possible to set up document analysis pipelines that form the basis for reproducible protocols. Since the platform keeps track of all intermediate results, it becomes an information resource for the analysis of experimental data.
Des robots pour les PME. Sécurité collaborative et intégration des robots en PME (Performances, 9... more Des robots pour les PME. Sécurité collaborative et intégration des robots en PME (Performances, 9Q145) La majeure partie des robots implantés dans le monde aujourd'hui, c'est-à-dire plus d'un million, est utilisée par les grandes entreprises. C'est pourquoi dans ...
This contest aims to provide a metric giving indications on the influence of individual document ... more This contest aims to provide a metric giving indications on the influence of individual document analysis stages to overall end-to-end applications. Contestants are provided with a full, working pipeline which operates on a page image to extract useful information. The pipeline is built with clearly identified analysis stages (e.g. binarization, skew detection, layout analysis, OCR ...) that have a formalized input and output. Contestants are invited to contribute their own algorithms as an alternative to one or more of the initially provided stages. The evaluation measures the overall impact of the contributed algorithm on the final (end-of-pipeline) output.
This contest aims to provide a metric giving indications on the influence of individual document ... more This contest aims to provide a metric giving indications on the influence of individual document analysis stages to overall end-to-end applications. Contestants are provided with a full, working pipeline which operates on a page image to extract useful information. The pipeline is built with clearly identified analysis stages (e.g. binarization, skew detection, layout analysis, OCR ...) that have a formalized input and output. Contestants are invited to contribute their own algorithms as an alternative to one or more of the initially provided stages. The evaluation measures the overall impact of the contributed algorithm on the final (end-of-pipeline) output.
International Journal of Pattern Recognition and Artificial Intelligence, 2014
In this paper, we address a new scheme for symbol retrieval based on bag-of-relations (BoRs) whic... more In this paper, we address a new scheme for symbol retrieval based on bag-of-relations (BoRs) which are computed between extracted visual primitives (e.g. circle and corner). Our features consist of pairwise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological relation information indexed in bags-of-relations and use this for recognition. As a consequence, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using several different well known datasets such as GREC, FRESH and SESYD, and includes a comparison with state-of-the-art descriptors. Experiments provide interesting results on symbol spotting and other user-friendly symbol retrieval applications.
International Journal of Pattern Recognition and Artificial Intelligence, 2013
In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the... more In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalisation based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behaviour by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.
2013 12th International Conference on Document Analysis and Recognition, 2013
In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BO... more In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BOFs) which are computed between the extracted visual primitives. Our feature consists of pairwise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological information to guide directional relations. Consequently, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using two different datasets. Experimental tests provide interesting results by establishing user-friendly symbol retrieval application.
International Journal on Document Analysis and Recognition, 2013
This paper develops a structural symbol recognition method with integrated statistical features. ... more This paper develops a structural symbol recognition method with integrated statistical features. It applies spatial organization descriptors to the identified shape features within a fixed visual vocabulary that compose a symbol. It builds an attributed relational graph expressing the spatial relations between those visual vocabulary elements. In order to adapt the chosen vocabulary features to multiple and possible specialized contexts, we study the pertinence of unsupervised clustering to capture significant shape variations within a vocabulary class and thus refine the discriminative power of the method. This unsupervised clustering relies on cross-validation between several different cluster indices. The resulting approach is capable of determining part of the pertinent vocabulary and significantly increases recognition results with respect to the state-of-the-art. It is experimentally validated on complex electrical wiring diagram symbols.
Abstract. In this paper we present a way to use precision and recall measures in total absence of... more Abstract. In this paper we present a way to use precision and recall measures in total absence of ground truth. We develop a probabilistic interpretation of both measures and show that, provided a sufficient number of data sources are available, it offers a viable performance measure to compare methods if no ground truth is available. This paper also shows the limitations of the approach, in case a systematic bias is present in all compared methods, but shows that it maintains a very high level of overall coherence and stability.
In this paper, we present a method for symbol recognition based on the spatio-structural descript... more In this paper, we present a method for symbol recognition based on the spatio-structural description of a 'vocabulary'of extracted visual elementary parts. It is applied to symbols in electrical wiring diagrams. The method consists of first identifying vocabulary elements into different groups based on their types (eg, circle, corner). We then compute spatial relations between the possible pairs of labelled vocabulary types which are further used as a basis for building an attributed relational graph that fully describes the symbol.
Abstract. In this paper we summarize the framework and the results of the fourth edition of the I... more Abstract. In this paper we summarize the framework and the results of the fourth edition of the International Symbol Recognition Contest, organized in the context of GREC'11. The contest follows the series started at the GREC'03 workshop and it is the first time that, in addition to recognition of isolated symbols, the contest includes the evaluation of symbol spotting.
The Document Analysis and Exploitation platform is a sophisticated technical environment that con... more The Document Analysis and Exploitation platform is a sophisticated technical environment that consists of a repository containing document images, implementations of document analysis algorithms, and the results of these algorithms when applied to data in the repository. The use of a webservices model makes it possible to set up document analysis pipelines that form the basis for reproducible protocols. Since the platform keeps track of all intermediate results, it becomes an information resource for the analysis of experimental data.
Des robots pour les PME. Sécurité collaborative et intégration des robots en PME (Performances, 9... more Des robots pour les PME. Sécurité collaborative et intégration des robots en PME (Performances, 9Q145) La majeure partie des robots implantés dans le monde aujourd'hui, c'est-à-dire plus d'un million, est utilisée par les grandes entreprises. C'est pourquoi dans ...
This contest aims to provide a metric giving indications on the influence of individual document ... more This contest aims to provide a metric giving indications on the influence of individual document analysis stages to overall end-to-end applications. Contestants are provided with a full, working pipeline which operates on a page image to extract useful information. The pipeline is built with clearly identified analysis stages (e.g. binarization, skew detection, layout analysis, OCR ...) that have a formalized input and output. Contestants are invited to contribute their own algorithms as an alternative to one or more of the initially provided stages. The evaluation measures the overall impact of the contributed algorithm on the final (end-of-pipeline) output.
This contest aims to provide a metric giving indications on the influence of individual document ... more This contest aims to provide a metric giving indications on the influence of individual document analysis stages to overall end-to-end applications. Contestants are provided with a full, working pipeline which operates on a page image to extract useful information. The pipeline is built with clearly identified analysis stages (e.g. binarization, skew detection, layout analysis, OCR ...) that have a formalized input and output. Contestants are invited to contribute their own algorithms as an alternative to one or more of the initially provided stages. The evaluation measures the overall impact of the contributed algorithm on the final (end-of-pipeline) output.
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Papers by Bart Lamiroy