Back to Search
Start Over
Finding Logo and Seal in Historical Document Images - An Object Detection Based Approach
- Source :
- Lecture Notes in Computer Science ISBN: 9783030414030, ACPR (1)
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- Logo and Seal serves the purpose of authenticating and referring to the source of a document. This strategy was also prevalent in the medieval period. Different algorithm exists for detection of logo and seal in document images. A close look into the present state-of-the-art methods reveals that those methods were focused toward detection of logo and seal in contemporary document images. However, such methods are likely to underperform while dealing with historical documents. This is due to the fact that historical documents are attributed with additional challenges like extra noise, bleed-through effect, blurred foreground elements and low contrast. The proposed method frames the problem of the logo and seals detection in an object detection framework. Using a deep-learning technique it counters earlier mentioned problems and evades the need for any pre-processing stage like layout analysis and/or binarization in the system pipeline. The experiments were conducted on historical images from 12th to the 16th century and the results obtained were very encouraging for detecting logo in historical document images. To the best of our knowledge, this is the first attempt on logo detection in historical document images using an object-detection based approach.
- Subjects :
- Seal (emblem)
Information retrieval
Computer science
business.industry
Logo
0102 computer and information sciences
02 engineering and technology
01 natural sciences
Pipeline (software)
Object detection
Low contrast
010201 computation theory & mathematics
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Noise (video)
Artificial intelligence
business
Historical document
Subjects
Details
- ISBN :
- 978-3-030-41403-0
- ISBNs :
- 9783030414030
- Database :
- OpenAIRE
- Journal :
- Lecture Notes in Computer Science ISBN: 9783030414030, ACPR (1)
- Accession number :
- edsair.doi...........69f03197bab6ec13d4491579275cd049