גהאד אלצאנע

אקדמי בכיר

The HHD Dataset

Irina Rabaev, Berat Kurar Barakat, Alexander Churkin, Jihad El-Sana

Benchmark datasets are important in document image processing field, as they allow to analyze different approaches and compare their performances in a fair manner. There exist benchmark datasets for several alphabets such as Latin, Arabic and Chinese, but not the Hebrew alphabet. In this paper, a handwritten Hebrew dataset, HHD, is introduced. The HHD dataset is collected from hand-filled forms, and accompanied by their ground truth at character, word and text line levels. Presently, the dataset contains around 1000 document images, and we continue to further enlarge it. To the best of our knowledge, this is the first comprehensive corpus of Hebrew handwritten documents, and we believe it will help leveraging Hebrew documents processing and document processing in general. The dataset can be useful for various research applications, such as word spotting, word recognition, text line alignment, and writer identification. The initial small subset of the HDD for character classification can be downloaded from https://www.cs.bgu.ac.illr-vberatldatalhhd-dataset.zip together with the training and test sets subdivisions. We also provide baseline results for character classification on this initial subset. In the near future, the full HHD dataset will be made freely available to the research community.

שפת פרסום אנגלית
דפים 228-233
סטטוס פרסום פורסם - 01.09.2020

Keywords

Ground truth
Handwritten document image dataset
Hebrew handwritten documents

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Computer Science Applications
גישה למסמך
10.1109/ICFHR2020.2020.00050
קבצים וקישורים אחרים
Link to publication in Scopus