This portal has been archived. Explore the next generation of this technology.
Font Acknowledgment and Character Extraction of Digital and Scanned Images
lib:1b1db7a64fca9a33 (v1.0.0)
Authors: Syed Muhammad Arsalan Bashir
ArXiv: 1305.4064
Document: PDF DOI
Abstract URL: http://arxiv.org/abs/1305.4064v1
The font recognition and character extraction is of immense importance as these are many scenarios where data are in such a form, which cannot be processed like in image form or as a hard copy. So the procedure developed in this paper is basically related to identifying the font (Times New Roman, Arial and Comic Sans MS) and afterwards recovering the text using simple correlation based method where the binary templates are correlated to the input image text characters. All of this extraction is done in the presence of a little noise as images may have noisy patterns due to photocopying. The significance of this method exists in extraction of data from various monitoring (Surveillance) camera footages or even more. The method is developed on Matlab\c{opyright} which takes input image and recovers text and font information from it in a text file.
ArXiv: 1305.4064
Document: PDF DOI
Abstract URL: http://arxiv.org/abs/1305.4064v1
The font recognition and character extraction is of immense importance as these are many scenarios where data are in such a form, which cannot be processed like in image form or as a hard copy. So the procedure developed in this paper is basically related to identifying the font (Times New Roman, Arial and Comic Sans MS) and afterwards recovering the text using simple correlation based method where the binary templates are correlated to the input image text characters. All of this extraction is done in the presence of a little noise as images may have noisy patterns due to photocopying. The significance of this method exists in extraction of data from various monitoring (Surveillance) camera footages or even more. The method is developed on Matlab\c{opyright} which takes input image and recovers text and font information from it in a text file.
Relevant initiatives
Related knowledge about this paper
Reproduced results (crowd-benchmarking and competitions)
Artifact and reproducibility checklists
- ACM/cTuning artifact appendix and reproducibility checklist
- NeurIPS reproducibility checklist
- SIGPLAN's checklist for empirical evaluation
- Collective Knowledge (organizing research projects based on FAIR principles)