IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
The grammar of dimensions in machine drawings
Computer Vision, Graphics, and Image Processing
Computer Vision, Graphics, and Image Processing
Performance of the Hough transform and its relationship to statistical signal detection theory
Computer Vision, Graphics, and Image Processing
Segmentation of edges into lines and arcs
Image and Vision Computing
A syntactic geometric approach to recognition of dimensions in engineering machine drawings
Computer Vision, Graphics, and Image Processing
Orthogonal zig-zag: an efficient method for extracting straight lines from engineering drawings
IAPR Proceedings of the international workshop on Visual form: analysis and recognition
Dimensioning analysis: toward automatic understanding of engineering drawings
Communications of the ACM
Finding circles by an array of accumulators
Communications of the ACM
Computer and Robot Vision
A System for Interpretation of Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Arc Segmentation Algorithm and Its Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Empirical Performance Evaluation of Graphics Recognition Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Syntactic and Semantic Graphics Recognition: The Role of the Object-Process Methodology
GREC '99 Selected Papers from the Third International Workshop on Graphics Recognition, Recent Advances
Document Analysis Systems Development and Representation through the Object-Process Methodology
DAS '98 Selected Papers from the Third IAPR Workshop on Document Analysis Systems: Theory and Practice
TIF2VEC, An Algorithm for Arc Segmentation in Engineering Drawings
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
ERP modeling: a comprehensive approach
Information Systems
Effective Multiresolution Arc Segmentation: Algorithms and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Aligning an ERP system with enterprise requirements: an object-process based approach
Computers in Industry - Special issue: Current trends in ERP implementations and utilisation
ARG Based on Arcs and Segments to Improve the Symbol Recognition by Genetic Algorithm
Graphics Recognition. Recent Advances and New Opportunities
Aligning an ERP system with enterprise requirements: An object-process based approach
Computers in Industry - Special issue: Current trends in ERP implementations and utilisation
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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Arcs are important primitives in engineering drawings. Along with bars, they play a major role in describing both the geometry and the annotation of the object represented in the drawing. Extracting these primitives during the lexical analysis phase is a prerequisite to syntactic and semantic understanding of engineering drawings within the Machine Drawing Understanding System. Bars are detected by the orthogonal zig-zag vectorization algorithm. Some of the detected bars are linear approximations of arcs. As such, they provide the basis for arc segmentation. An arc is detected by finding a chain of bars and a triplet of points along the chain. The arc center is first approximated as the center of mass of the triangle formed by the intersection of the perpendicular bisectors of the chords these points define. The location of the center is refined by recursively finding more such triplets and converging to within no more than a few pixels from the actual arc center after two or three iterations. The high performance of the algorithm, demonstrated on a set of real engineering drawings, is due to the fact that it avoids both raster-to-vector and massive pixel-level operations, as well as any space transformations.