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Author |
Mathieu Nicolas Delalandre; Jean-Marc Ogier; Josep Llados |
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Title |
A Fast Cbir System of Old Ornamental Letter |
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Book Chapter |
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Year |
2008 |
Publication |
Graphics Reognition: Recent Advances and New Opportunities |
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5046 |
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135–144 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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Call Number |
DAG @ dag @ DOL2008 |
Serial |
987 |
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Author |
Mathieu Nicolas Delalandre; Tony Pridmore; Ernest Valveny; Herve Locteau; Eric Trupin |
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Title |
Building Synthetic Graphical Documents for Performance Evaluation |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
288–298 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG @ dag @ DPV2008 |
Serial |
988 |
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Author |
Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez; Joan Mas |
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Title |
Hand Drawn Symbol Recognition by Blurred Shape Model Descriptor and a Multiclass Classifier |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
30–40 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG; HUPBA; MILAB |
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no |
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BCNPCL @ bcnpcl @ FEL2008 |
Serial |
989 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Old Handwritten Musical Symbol Classification by a Dynamic TimeWrapping Based Method |
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Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
52–60 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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Call Number |
DAG @ dag @ FLS2008a |
Serial |
990 |
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Author |
Joan Mas; J.A. Jorge; Gemma Sanchez; Josep Llados |
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Title |
Representing and Parsing Sketched Symbols using Adjacency Grammars and a Grid-Directed Parser |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities, |
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Volume |
5046 |
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Pages |
176–187 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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DAG @ dag @ MJS2008 |
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991 |
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Author |
Partha Pratim Roy; Eduard Vazquez; Josep Llados; Ramon Baldrich; Umapada Pal |
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Title |
A System to Segment Text and Symbols from Color Maps |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition. Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
245-256 |
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DAG;CIC |
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no |
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Call Number |
CAT @ cat @ RVL2008 |
Serial |
1005 |
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Author |
Josep Llados; Marçal Rusiñol |
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Title |
Graphics Recognition Techniques |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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Volume |
D |
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Pages |
489-521 |
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Keywords |
Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
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Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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Springer London |
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Editor |
D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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Notes |
DAG; 600.077 |
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Call Number |
Admin @ si @ LlR2014 |
Serial |
2380 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Categorization of Digital Ink Elements using Spectral Features |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
188–198 |
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Springer–Verlag |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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Call Number |
DAG @ dag @ RSL2008 |
Serial |
1099 |
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Author |
Josep Llados; Jaime Lopez-Krahe; Enric Marti |
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Title |
A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform |
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Book Chapter |
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Year |
1997 |
Publication |
Machine Vision and Applications |
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10 |
Issue |
3 |
Pages |
150-158 |
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Keywords |
Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition |
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Abstract |
Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input. |
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DAG;IAM |
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IAM @ iam @ LLM1997a |
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1566 |
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Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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Title |
Symbol recognition: current advances and perspectives |
Type |
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Year |
2002 |
Publication |
Graphics Recognition Algorithms And Applications |
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Volume |
2390 |
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Pages |
104-128 |
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Abstract |
The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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London, UK |
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Springer-Verlag |
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Dorothea Blostein and Young- Bin Kwon |
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Lecture Notes in Computer Science |
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3-540-44066-6 |
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GREC |
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DAG; IAM; |
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Call Number |
IAM @ iam @ LVS2002 |
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1572 |
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