A document image analysis toolbox, including a collection of data structures and algorithms to suppbrt a variety of applications, is described in this paper. An experimental environment is built to allow developers to develop, test and optimize their algorithms and systems. Appropriate and quantitative performance metrics for each kind of information a document analysis technique infers have been developed, The performance of each algorithm has been evaluatd based o n these metrics and the UW-III document image database which contains a total of 1600 English document images randomly selected from scientific and technical journals.

A b s t r a c t . This paper defines a computational protocol for evaluating the performance of raster to vector conversion systems. The graphical entities handled by this protocol are continuous and dashed lines, ares, and circles, and text regions. The protocol allows matches of the type one-to-one, one-to-many, and many-to-one between the ground truth and the recognition results.

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This paper presents an eficient technique for document page layout structure extraction and classification by analyzing the spatial configuration of the bounding boxes of different entzties on the given image. The algorithm segments an image into a list of homogeneous zones. The classification algorithm labels each zone as text, table, line-drawing, halftone, ruling, or noise. The text-lines and words are extracted within text zones and neighboring text-lines are merged to form text-blocks. The tabular structure is further decomposed into row and column items. Finally, the document layout hierarchy is produced from these extracted entities.

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