Title :
Robust and accurate vectorization of line drawings
Author :
Hilaire, Xavier ; Tombre, Karl
Author_Institution :
LORIA, Villers-Nancy, France
fDate :
6/1/2006 12:00:00 AM
Abstract :
This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector´s parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.
Keywords :
document image processing; image segmentation; sampling methods; accurate vectorization; graphical vectorization part; homogeneous thickness; input binary image; paper-based line drawings; performance analysis; random sampling; robust vectorization; segmentation method; Graphics; History; Image sampling; Image segmentation; Noise robustness; Performance analysis; Skeleton; Software packages; Software prototyping; Technical drawing; Document analysis; curve segmentation; graphics recognition and interpretation; line drawings.; performance evaluation; vectorization; Algorithms; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2006.127