抄録
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.
本文言語 | English |
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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 |
巻 | 16 |
号 | 2 |
DOI | |
出版ステータス | Published - 1994 2月 |
外部発表 | はい |
ASJC Scopus subject areas
- ソフトウェア
- コンピュータ ビジョンおよびパターン認識
- 計算理論と計算数学
- 人工知能
- 応用数学