Improved ring radius transform-based reconstruction for video character recognition
Document Type
Article
Publication Date
6-15-2021
Abstract
Character shape reconstruction in video is challenging due to low contrast, complex backgrounds and arbitrary orientation of characters. This work proposes an Improved Ring Radius Transform (IRRT) for reconstructing impaired characters through medial axis prediction. At first, the technique proposes a novel idea based on the Tangent Vector (TV) concept that identifies each actual pair of end pixels caused by gaps in impaired character components. Next, the actual direction to predict medial axis pixels using IRRT for each pair of end pixels is proposed with a new normal vector concept. The process of prediction repeats iteratively to find all the medial axis pixels for every gap in question. Further, medial axis pixels with their radii are used to reconstruct the shapes of impaired characters. The proposed technique is tested on benchmark datasets consisting of video, natural scenes, objects and multi-lingual data to demonstrate that it reconstructs shapes well, even for heterogeneous data. Comparative studies with different binarization and character recognition methods show that the proposed technique is effective, useful and outperforms existing methods.
Keywords
Video character recognition, Reconstruction, Ring radius transform
Divisions
Computer
Funders
National Natural Science Foundation of China (NSFC) [61672273],Ministry of Higher Education (DP KPT), Kuala Lumpur, Malaysia [FRGS-1-2020]
Publication Title
International Journal of Pattern Recognition and Artificial Intelligence
Volume
35
Issue
07
Publisher
World Scientific Publ Co Pte Ltd
Publisher Location
5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE