A new visual signature for content-based indexing of low resolution documents
This paper proposes a new visual signature for content –based indexing of low resolution documents. Camera Based Document Analysis and Recognition (CBDAR) has been established which deals with the textual information in scene images taken by low cost hand held devices like digital camera, cell p...
| Hoofdauteurs: | , , , |
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| Formaat: | Artikel |
| Taal: | English |
| Gepubliceerd in: |
2012
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| Onderwerpen: | |
| Online toegang: | http://eprints.uthm.edu.my/7097/1/J14168_5130d0b6fdee9bb0e61a4edec1d3837d.pdf |
| _version_ | 1825710313511583744 |
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| author | Md Nor, Danial Abd. Wahab, M. Helmy M. Jenu, M. Zarar Ogier, Jean-Marc |
| author_facet | Md Nor, Danial Abd. Wahab, M. Helmy M. Jenu, M. Zarar Ogier, Jean-Marc |
| author_sort | Md Nor, Danial |
| collection | UTHM |
| description | This paper proposes a new visual signature for content –based indexing of low resolution documents. Camera Based Document Analysis and Recognition (CBDAR) has been established which deals with
the textual information in scene images taken by low cost hand held devices like digital camera, cell
phones, etc. A lot of applications like text translation, reading text for visually impaired and blind
person, information retrieval from media document, e-learning, etc., can be built using the techniques
developed in CBDAR domain. The proposed approach of extraction of textual information is
composed of three steps: image segmentation, text localization and extraction, and Optical Character
Recognition. First of all, for pre-processing the resolution of each image is checked for re-sampling
to a common resolution format (720 X 540). Then, the final image is converted to grayscale and
binarized using Otsu segmentation method for further processing. In addition, looking at the mean
horizontal run length of both black and white pixels, the proper segmentation of foreground objects is
checked. In the post-processing step, the text localizer validates the candidate text regions proposed
by text detector. We have employed a connected component approach for text localization. The
extracted text is then has been successfully recognized using ABBYY FineReader for OCR. Apart
from OCR, we had created a novel feature vectors from textual information for Content-Based Image
Retrieval (CBIR). |
| first_indexed | 2024-03-05T21:55:43Z |
| format | Article |
| id | uthm.eprints-7097 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:55:43Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | uthm.eprints-70972022-06-08T02:05:28Z http://eprints.uthm.edu.my/7097/ A new visual signature for content-based indexing of low resolution documents Md Nor, Danial Abd. Wahab, M. Helmy M. Jenu, M. Zarar Ogier, Jean-Marc T Technology (General) This paper proposes a new visual signature for content –based indexing of low resolution documents. Camera Based Document Analysis and Recognition (CBDAR) has been established which deals with the textual information in scene images taken by low cost hand held devices like digital camera, cell phones, etc. A lot of applications like text translation, reading text for visually impaired and blind person, information retrieval from media document, e-learning, etc., can be built using the techniques developed in CBDAR domain. The proposed approach of extraction of textual information is composed of three steps: image segmentation, text localization and extraction, and Optical Character Recognition. First of all, for pre-processing the resolution of each image is checked for re-sampling to a common resolution format (720 X 540). Then, the final image is converted to grayscale and binarized using Otsu segmentation method for further processing. In addition, looking at the mean horizontal run length of both black and white pixels, the proper segmentation of foreground objects is checked. In the post-processing step, the text localizer validates the candidate text regions proposed by text detector. We have employed a connected component approach for text localization. The extracted text is then has been successfully recognized using ABBYY FineReader for OCR. Apart from OCR, we had created a novel feature vectors from textual information for Content-Based Image Retrieval (CBIR). 2012 Article PeerReviewed text en http://eprints.uthm.edu.my/7097/1/J14168_5130d0b6fdee9bb0e61a4edec1d3837d.pdf Md Nor, Danial and Abd. Wahab, M. Helmy and M. Jenu, M. Zarar and Ogier, Jean-Marc (2012) A new visual signature for content-based indexing of low resolution documents. Journal of Information Retrieval and Knowledge Management, 2. pp. 88-95. |
| spellingShingle | T Technology (General) Md Nor, Danial Abd. Wahab, M. Helmy M. Jenu, M. Zarar Ogier, Jean-Marc A new visual signature for content-based indexing of low resolution documents |
| title | A new visual signature for content-based indexing of low resolution documents |
| title_full | A new visual signature for content-based indexing of low resolution documents |
| title_fullStr | A new visual signature for content-based indexing of low resolution documents |
| title_full_unstemmed | A new visual signature for content-based indexing of low resolution documents |
| title_short | A new visual signature for content-based indexing of low resolution documents |
| title_sort | new visual signature for content based indexing of low resolution documents |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/7097/1/J14168_5130d0b6fdee9bb0e61a4edec1d3837d.pdf |
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