Morphological approach to character recognition in machine-printed Persian words
Bijan Timsari, Hamid Fahimi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
Based on the capabilities of morphological operators in extracting shape features, a new method for character recognition in Persian machine printed documents is introduced. Given the image of a printed character is available with high enough SNR such that its regular shape is preserved, some common primitive patterns can always be found after thinning different images of a single character. This property has inspired the development of our morphological processing in which the hit-or-miss operator is used to determine which patterns exist or do not exist in the input images of the recognition system. All the required processing before feature extraction including image enhancement, segmentation, and thinning are also performed using the hit-or-miss operator. Having the input words described in terms of some pre-defined patterns, the system knowledge base, holding descriptions for all characters, is searched for possible matches. Finding a match ends in the recognition of a character. This approach is proved to be fast and reliable in practice.