|
|
Gemma Sanchez, Alicia Fornes, Joan Mas and Josep Llados. 2007. Computer Vision Tools for Visually Impaired Children Learning.
|
|
|
|
Gemma Sanchez, Alicia Fornes, Joan Mas and Josep Llados. 2007. Computer Vision Tools for Visually Impaired Children Learning.
|
|
|
|
Gemma Sanchez and 6 others. 2003. A system for virtual prototyping of architectural projects. Proceedings of Fifth IAPR International Workshop on Pattern Recognition.65–74.
|
|
|
|
Gemma Sanchez, Ernest Valveny, Josep Llados, Joan Mas and N. Lozano. 2004. A platform to extract knowledge from graphic documents. Application to an architectural sketch understanding scenario.
|
|
|
|
Gemma Sanchez and Josep Llados. 2001. A Graph Grammar to Recognize Textured Symbols..
|
|
|
|
Gemma Sanchez and Josep Llados. 2003. Syntactic models to represent perceptually regular repetitive patterns in graphic documents.
|
|
|
|
Gemma Sanchez and Josep Llados. 2004. Syntactic models to represent perceptually regular repetitive patterns in graphic documents.
|
|
|
|
Gemma Sanchez, Josep Llados and Enric Marti. 1997. A string-based method to recognize symbols and structural textures in architectural plans. 2nd IAPR Workshop on Graphics Recognition.
Abstract: This paper deals with the recognition of symbols and struc- tural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clus- tering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the simila- rity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
|
|
|
|
Gemma Sanchez, Josep Llados and Enric Marti. 1997. Segmentation and analysis of linial texture in plans. Intelligence Artificielle et Complexité.. Paris.
Abstract: The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph.
Keywords: Structural Texture, Voronoi, Hierarchical Clustering, String Matching.
|
|
|
|
Gemma Sanchez, Josep Llados and K. Tombre. 2001. An Algorithm to Recognize Graphical Textured Symbols using String Representations..
|
|
