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Character Segmentation and Recognition Algorithm for Various Text Region Images  

Koo, Keun-Hwi (포항공대 전자전기공학과)
Choi, Sung-Hoo (포항공대 전자전기공학과)
Yun, Jong-Pil (포항공대 전자전기공학과)
Choi, Jong-Hyun (포항공대 전자전기공학과)
Kim, Sang-Woo (포항공대 전자전기공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.58, no.4, 2009 , pp. 806-816 More about this Journal
Abstract
Character recognition system consists of four step; text localization, text segmentation, character segmentation, and recognition. The character segmentation is very important and difficult because of noise, illumination, and so on. For high recognition rates of the system, it is necessary to take good performance of character segmentation algorithm. Many algorithms for character segmentation have been developed up to now, and many people have been recently making researches in segmentation of touching or overlapping character. Most of algorithms cannot apply to the text regions of management number marked on the slab in steel image, because the text regions are irregular such as touching character by strong illumination and by trouble of nozzle in marking machine, and loss of character. It is difficult to gain high success rate in various cases. This paper describes a new algorithm of character segmentation to recognize slab management number marked on the slab in the steel image. It is very important that pre-processing step is to convert gray image to binary image without loss of character and touching character. In this binary image, non-touching characters are simply separated by using vertical projection profile. For separating touching characters, after we use combined profile to find candidate points of boundary, decide real character boundary by using method based on recognition. In recognition step, we remove noise of character images, then recognize respective character images. In this paper, the proposed algorithm is effective for character segmentation and recognition of various text regions on the slab in steel image.
Keywords
Character segmentation; Recognition; Various text region; Steel image; Management number;
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