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A framework for object recognition in a visually complex environment and its application to locating address blocks on mail pieces

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Abstract

A computational framework for recognizing an object of interest in a complex visual environment is described. Arising from the problem of finding the destination address block on a mail piece, a general framework for coordinating a collection of specialized image-analysis tools is described. The resulting system is capable of dealing with a wide range of environments—from those having a high degree of global spatial structure (e.g., letter mail envelopes that conform to specifications) to those with no structure (e.g., magazines with randomly pasted address labels). The problem-solving architecture accounts for uncertainty in the imaging environment by using the blackboard model. This paper discusses systematic derivation of a set of object recognition heuristics (knowledge base), specialized image analysis tools for extracting those features that are called for by the heuristics, and a control structure for integrating evidence and managing tools. Experimental results with a database of difficult cases demonstrating the promise of the methodology are presented.

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Authors and Affiliations

  1. Department of Computer Science, State University of New York at Buffalo, 14260, Buffalo, NY

    Ching-Huei Wang & Sargur N. Srihari

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  1. Ching-Huei Wang
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  2. Sargur N. Srihari
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Additional information

This work was supported by the Office of Advanced Technology of the United States Postal Service Under Task Order 104230-85-M3349.

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Wang, CH., Srihari, S.N. A framework for object recognition in a visually complex environment and its application to locating address blocks on mail pieces. Int J Comput Vision 2, 125–151 (1988). https://doi.org/10.1007/BF00133697

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