Recognition of handwritten and machine-printed text for postal address interpretation
Pattern Recognition Letters - Postal processing and character recognition
Combining Multiple OCRs for Optimizing Word Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
A new system for reading handwritten zip codes
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
IEA/AIE '00 Proceedings of the 13th international conference on Industrial and engineering applications of artificial intelligence and expert systems: Intelligent problem solving: methodologies and approaches
Optical Character Recognition for Cursive Handwriting
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Digital Library Systems
| Hi-index | 0.00 |
This paper presents a cursive handwritten address recognition system, which consists of four main modules: (i) over-segmentor, (ii) dynamic zip locator, (iii) zip candidates generator, and (iv) city-state-zip verifier. The dynamic zip locator and city-state-zip verifier are based on a flexible matcher for matching a sequence of graphemes with a list of generalized strings. The dynamic zip locator is able to locate zip without knowing exactly where the zip starts. The zip candidates generator uses a hidden Markov model (HMM) with position-dependent state transition probabilities. A scheme for utilizing prefixes is designed to reduce computation and memory requirement. Finally, the system employs a mechanism for rejection based on rank features extracted from the matching. The overall system achieves an acceptance rate of 83.5% with 3.6% error for 5-digit encoding on 805 USPS cursive address images.