Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming

Bodic, Pierre Le; Locteau, Hervé; Adam, Sébastien; Héroux, Pierre; Lecourtier, Yves; Knippel, Arnaud

doi:10.1109/icdar.2009.202

Cited by 16 publications

(20 citation statements)

References 7 publications

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“…Formulating the linear program is now done, and all that is needed is an efficient solver to work on it. The testing done in (LeBodic, et al 2009) is on very application-specific instances (architectural floor plans) making it difficult to evaluate in terms of the more general instances seen in the graph databases.…”

Section: Resultsmentioning

confidence: 99%

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Investigation of Zero Knowledge Proof Approaches Based on Graph Theory

Horan¹,

Gudaitis²

2011

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Section: Resultsmentioning

confidence: 99%

“…One such approach formulates the sub-graph isomorphism problem as an integer linear program (LeBodic, et al 2009). We define the variables of this linear program as follows.…”

Section: Resultsmentioning

confidence: 99%

Investigation of Zero Knowledge Proof Approaches Based on Graph Theory

Horan¹,

Gudaitis²

2011

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“…Attributed Relational Graphs (ARGs) can be used to describe the primitives, their associated attributes and interconnections. However, subgraph isomorphism is known to be a NP-hard problem, making it difficult to use the graph for large images and document collections, despite the approximate solutions of subgraph isomorphism developed in the literature [2], [9]. In addition, subgraph isomorphism remains very sensitive to the robustness of the feature extraction step, as any wrong detection can result in strong distortions in the ARGs.…”

Section: Introductionmentioning

confidence: 98%

Robust Symbol Localization Based on Junction Features and Efficient Geometry Consistency Checking

Pham¹,

Delalandre²,

Barrat³

et al. 2013

2013 12th International Conference on Document Analysis and Recognition

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This paper presents a new approach for symbol localization in line-drawing images using junction features and geometry consistency checking. The proposed system first detects junction points, and then characterizes them by very compact, distinctive, and varying-length descriptors. The detected junctions are used to decompose a document image into a set of smooth primitives composing of isolated shapes (e.g., isolated circles and straight lines) and curve segments bounded between either two junctions or a junction and an end-point. These primitives are then associated with a new set of keypoints to form a complete and compact representation of a graphical document. Next, keypoint matching is performed to find the correspondences among the keypoints of the query and those of database documents. The obtained matches are finally refined by a new and efficient algorithm to deal with the problem of geometry consistency checking. Our experiments showed that the proposed system is very time-and memory-efficient, and provides high accuracy rate of symbol localization.

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“…This original approach is parameter free and solves problems that could not be solved optimally using existing algorithms. This paper is an extended and improved version of [13]. The new contributions concern an extension of the approach for the search for multiple solutions and a strategy that enables the learning of a threshold for this search.…”

Section: Introductionmentioning

confidence: 99%

An integer linear program for substitution-tolerant subgraph isomorphism and its use for symbol spotting in technical drawings

Bodic

Héroux

Adam

et al. 2012

Pattern Recognition

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This paper tackles the problem of substitution-tolerant subgraph isomorphism which is a specific class of error-tolerant isomorphism. This problem aims at finding a subgraph isomorphism of a pattern graph S in a target graph G. This isomorphism only considers label substitutions and forbids vertex and edge insertion in G. This kind of subgraph isomorphism is often needed in pattern recognition problems when graphs are attributed with real values and no exact matching can be found between attributes due to noise.Our proposal to solve the problem of substitution-tolerant subgraph isomorphism relies on its formulation in the Integer Linear Program (ILP) formalism. Using a general ILP solver, the approach is able to find, if one exists, a mapping of a pattern graph into a target graph such that the topology of the searched graph is kept and the editing operations between the labels have a minimal cost.This technique is evaluated on both a set of synthetic graphs and a problem of symbol detection in technical drawings. In the second case, document and symbol images are represented by vector-attributed Region Adjacency Graphs built from a segmentation process. Obtained results demonstrate the relevance of considering subgraph isomorphism as an optimization process.

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Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming

Cited by 16 publications

References 7 publications

Investigation of Zero Knowledge Proof Approaches Based on Graph Theory

Investigation of Zero Knowledge Proof Approaches Based on Graph Theory

Robust Symbol Localization Based on Junction Features and Efficient Geometry Consistency Checking

An integer linear program for substitution-tolerant subgraph isomorphism and its use for symbol spotting in technical drawings

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