The automatic recognition of hand written text is an important practical problem with a great variety of potential applications: fax reading, form reading, help to blind people, signature verification, check reading, code recognition, address reading, document database population, and many more. Therefore, the interest of academic groups and commercial associations in hand written recognition is high. In this state of the art review, we address the field of the off-line recognition of unconstrained hand printed characters. We illustrate the results of two comparative tests of ICR systems conducted by NIST: the first deals with the recognition of isolated hand printed characters and the second with the reading of hand printed words from U.S. census forms. Starting from these results and from our experience, we focus our attention on the available commercial products we consider the most reliable. Finally, we present recent trends of the academic research in this area of machine vision, aiming at identifying the most challenging fields for future research
Review of the State of the Art in Optical Character Recognition. Part 2: Hand Printed Documents
Messelodi, Stefano;Modena, Carla Maria
1996-01-01
Abstract
The automatic recognition of hand written text is an important practical problem with a great variety of potential applications: fax reading, form reading, help to blind people, signature verification, check reading, code recognition, address reading, document database population, and many more. Therefore, the interest of academic groups and commercial associations in hand written recognition is high. In this state of the art review, we address the field of the off-line recognition of unconstrained hand printed characters. We illustrate the results of two comparative tests of ICR systems conducted by NIST: the first deals with the recognition of isolated hand printed characters and the second with the reading of hand printed words from U.S. census forms. Starting from these results and from our experience, we focus our attention on the available commercial products we consider the most reliable. Finally, we present recent trends of the academic research in this area of machine vision, aiming at identifying the most challenging fields for future researchI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
