Analysis of Technical Documents: The REDRAW System

Antoine, Dominique; Collin, Suzanne; Tombre, Karl

doi:10.1007/978-3-642-77281-8_18

Cited by 34 publications

(16 citation statements)

References 15 publications

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“…The problem of arc detection was recently studied in [77] proposing a method that combines two of the most reliable techniques in the literature. Hatched pattern detection is an important concern in the field of document analysis [78,69,73] and is usually solved by clustering parallel lines having the same slope angle and sorting them along a normal direction. Dimensions usually follow strict standards.…”

Section: Engineering Drawingsmentioning

confidence: 99%

See 1 more Smart Citation

Symbol Recognition: Current Advances and Perspectives

Lladós¹,

Valveny²,

Sánchez³

et al. 2002

Lecture Notes in Computer Science

102

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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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Section: Engineering Drawingsmentioning

confidence: 99%

“…From a general point of view, we could define three types of maps which have their own notational conventions. At the lowest level of difficulty, we could place cadastral city maps [69,55,79,70]. In such type of documents, symbols have a polygonal shape often filled by a hatching pattern.…”

Section: Mapsmentioning

confidence: 99%

Symbol Recognition: Current Advances and Perspectives

Lladós¹,

Valveny²,

Sánchez³

et al. 2002

Lecture Notes in Computer Science

102

View full text Add to dashboard Cite

show abstract

“…-Cadastral maps with the Redraw system [13]. In this early work, contextual knowledge about the city maps we wanted to analyze was embedded in the recognition process, through simple heuristics on the kinds of features we were interested in: hatched areas representing buildings, closed areas with labels corresponding to land parcels, streets, etc.…”

Section: Recognitionmentioning

confidence: 99%

Pattern Recognition Methods for Querying and Browsing Technical Documentation

Tombre

2008

Lecture Notes in Computer Science

Self Cite

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To cite this version:Karl Tombre, Bart Lamiroy. Abstract. Graphics recognition deals with the specific pattern recognition problems found in graphics-rich documents, typical technical documentation of all kinds. In this paper, we propose a short journey through 20 years of involvement and contributions within this scientific community, and explore more precisely a few interesting issues found when the problem is to browse, query and navigate in a large and complex set of technical documents.

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“…Tracking and matching opposite contours is an alternative technique that was tested in the late 80's [1], [36]. It provides correct and accurate results if the junctions are simple.…”

Section: A Finding the Lines: Raster-to-vector Conversionmentioning

confidence: 99%