A Robust Table Detection Method for Distortion in Image Acquired from Camera

Toshiya Nakaigawa, Yoshiki Mashiyama, Yasue Mitsukura, Nozomu Hamada

研究成果: Conference contribution

抄録

In this paper, the robust table detection method for distortion is proposed in image acquired by camera. Images acquired by the camera contain distortion due to the curvature of the paper and it makes difficult to detect the table in images. In order to address this issue, a method of dividing the frame line of the table in the vertical direction and the horizontal direction and detecting the frame lines by curve approximation in each direction is proposed. Dividing the frame lines in each direction, it is possible to simplify the multiple curve detection. As a result, the lines detection accuracy in the curved surface image was 99.4%. In addition, similar results were obtained for curved images rotated by 90°. This method can cope with distortion in both the vertical and horizontal directions. From these results, it was confirmed the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトルProceedings
ホスト出版物のサブタイトルIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
出版社IEEE Computer Society
ページ5347-5352
ページ数6
ISBN(電子版)9781728148786
DOI
出版ステータスPublished - 2019 10
イベント45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
継続期間: 2019 10 142019 10 17

出版物シリーズ

名前IECON Proceedings (Industrial Electronics Conference)
2019-October

Conference

Conference45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
国/地域Portugal
CityLisbon
Period19/10/1419/10/17

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 電子工学および電気工学

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