Recognizing Characters in Scene Images

Jun Ohya, Akio Shio, Shigeru Akamatsu

研究成果: Article

171 引用 (Scopus)

抜粋

An effective algorithm for character recognition in scene images is studied. Scene images are segmented into regions by an image segmentation method based on adaptive thresholding. Character candidate regions are detected by observing gray-level differences between adjacent regions. To ensure extraction of multisegment characters as well as single-segment characters, character pattern candidates are obtained by associating the detected regions according to their positions and gray levels. A character recognition process selects patterns with high similarities by calculating the similarities between character pattern candidates and the standard patterns in a dictionary and then comparing the similarities to the thresholds. A relaxational approach to determine character patterns updates the similarities by evaluating the interactions between categories of patterns, and finally character patterns and their recognition results are obtained. Highly promising experimental results have been obtained using the method on 100 images involving characters of different sizes and formats under uncontrolled lighting.

元の言語English
ページ(範囲)214-220
ページ数7
ジャーナルIEEE Transactions on Pattern Analysis and Machine Intelligence
16
発行部数2
DOI
出版物ステータスPublished - 1994 2
外部発表Yes

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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