Title :
Evaluating spatial correspondence of zones in document recognition systems
Author :
Garris, Michael D.
Author_Institution :
Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
Abstract :
This paper introduces scoring methods developed to automatically assess the performance of document recognition systems, specifically, to evaluate the spatial correspondence of zones produced by a document segmentor. Two different approaches are discussed. The first approach (based on zone overlap and nearest-neighbors) is better applied to merged zones, whereas the second approach (based on zone alignments) is better applied to nested zones (such as those found in tables and graphs). Definitions of coverage and efficiency error are presented, and scoring results on real system output is provided that validates the usefulness of these methods to compare different document recognition algorithms. Currently, no standard testing procedures exist for measuring and comparing algorithms within a complex document recognition system. Scoring methods, like the ones introduced in this paper, serve as design and validations tools, expediting the development and deployment of document analysis technology for system developers and end users
Keywords :
document image processing; image recognition; image segmentation; coverage; design tools; document analysis technology; document recognition algorithms; document recognition systems; document segmentor; efficiency error; graphs; merged zones; nearest neighbors; nested zones; scoring methods; scoring results; spatial correspondence; system output; tables; validations tools; zone alignments; zone overlap; Algorithm design and analysis; Current measurement; Measurement standards; NIST; Optical character recognition software; Optical filters; Performance analysis; Standards development; System testing; Text analysis;
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
DOI :
10.1109/ICIP.1995.537637