Khatt: Arabic offline handwritten text database
2012 International conference on frontiers in handwriting recognition, 2012•ieeexplore.ieee.org
In this paper, we report our comprehensive Arabic offline Handwritten Text database
(KHATT) after completion of the collection of 1000 handwritten forms written by 1000 writers
from different countries. It is composed of an image database containing images of the
written text at 200, 300, and 600 dpi resolutions, a manually verified ground truth database
that contains meta-data describing the written text at the page, paragraph, and line levels. A
formal verification procedure is implemented to align the handwritten text with its ground …
(KHATT) after completion of the collection of 1000 handwritten forms written by 1000 writers
from different countries. It is composed of an image database containing images of the
written text at 200, 300, and 600 dpi resolutions, a manually verified ground truth database
that contains meta-data describing the written text at the page, paragraph, and line levels. A
formal verification procedure is implemented to align the handwritten text with its ground …
In this paper, we report our comprehensive Arabic offline Handwritten Text database (KHATT) after completion of the collection of 1000 handwritten forms written by 1000 writers from different countries. It is composed of an image database containing images of the written text at 200, 300, and 600 dpi resolutions, a manually verified ground truth database that contains meta-data describing the written text at the page, paragraph, and line levels. A formal verification procedure is implemented to align the handwritten text with its ground truth at the form, paragraph and line levels. Tools to extract paragraphs from pages and segment paragraphs into lines are developed. Preliminary experiments on Arabic handwritten text recognition are conducted using sample data from the database and the results are reported. The database will be made freely available to researchers world-wide for research in various handwritten-related problems such as text recognition, writer identification and verification, etc.
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