@inproceedings{fca1c16953f0499c8f3230da347915c8,
title = "Dotted and curved line character segmentation",
abstract = "This paper presents new methodology for addressing curvature and segmentation in text as applied to dotted line images. Several improvements are provided, including methods and procedures for handling (a) curvature in text detection and segmentation, (b) rotation angle determinations, (c) isolation of only the character pixels in the image, (d) use of a fill algorithm to solidify the dotted character, and (e) discernment of segmented characters which may be printed too closely or that touch each other. Applying the new algorithms under various lighting conditions against 90 water bottle images (from Ozarka{\textregistered} and Dasani{\textregistered}) with differing text yielded a 93% accuracy rate. Additionally, the fill algorithm presented here improved recognition by more than 20% as compared to non-filled characters.",
keywords = "Angled text, Character recognition, Connected characters, Dotted character, Fill pixels image, Rotation, Segmentation",
author = "Khader Mohammad and Sos Agaian and Hani Saleh",
year = "2011",
doi = "10.1117/12.871730",
language = "British English",
isbn = "9780819484154",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Intelligent Robots and Computer Vision XXVIII",
note = "Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques ; Conference date: 24-01-2011 Through 25-01-2011",
}