Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Document image analysis
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
SLIDE: Subspace-Based Line Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-Level Component Grouping Algorithm and Its Applications
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Fiducial line based skew estimation
Pattern Recognition
A Figure Image Processing System
Graphics Recognition. Recent Advances and New Opportunities
Automatic Collection of Fuel Prices from a Network of Mobile Cameras
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
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The bounding-box of a geometric shape in 2D is the rectangle with the smallest area in a given orientation (usually upright) that complete contains the shape. The best-fit bounding-box is the smallest bounding-box among all the possible orientations for the same shape. In the context of document image analysis, the shapes can be characters (individual components) or paragraphs (component groups). This paper presents a search algorithm for the best-fit bounding-boxes of the textual component groups, whose shape are customarily rectangular in almost all languages. One of the applications of the best-fit bounding-boxes is the skew estimation from the text blocks in document images. This approach is capable of multi-skew estimation and location, as well as being able to process documents with sparse text regions. The University of Washington English Document Image Database (UW-I) is used to verify the skew estimation method directly and the proposed best-fit bounding-boxes algorithm indirectly.