Computer recognition of Arabic cursive scripts
Pattern Recognition
Recognition of Arabic Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Survey and bibliography of Arabic optical text recognition
Signal Processing
An Omnifont Open-Vocabulary OCR System for English and Arabic
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Role of Holistic Paradigms in Handwritten Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Handwritten Cursive Arabic Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keyword Spotting in Poorly Printed Documents using Pseudo 2-D Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 4th International Conference on Pattern Recognition
Using Hierarchical Shape Models to Spot Keywords in Cursive Handwriting Data
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Transcript Mapping for Historic Handwritten Document Images
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Structural Decomposition and Statistical Description of Farsi/Arabic Handwritten Numeric Characters
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Arabic Handwriting Recognition Using Baseline Dependant Features and Hidden Markov Modeling
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Searching Off-line Arabic Documents
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Retrieval of Ottoman documents
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Holistic approach for classifying and retrieving personal Arabic handwritten documents
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Segment confidence-based binary segmentation (SCBS) for cursive handwritten words
Expert Systems with Applications: An International Journal
Component retrieval based on a database of graphs for Hand-Written Electronic-Scheme Digitalisation
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Technologies for reading and searching digital documents have helped academic researchers; however, truly effective search engines for handwritten documents have not been developed. Recently, there is a growing need to access historical Arabic handwritten manuscripts (HAH manuscripts) that are stored in large archives; therefore, managing tools for automatic searching, indexing, classifying and retrieval of HAH manuscripts are required. The peculiar characteristics of Arabic handwriting have added an extra challenging dimension in developing such systems. This paper presents a novel holistic technique for classifying and retrieving HAH manuscripts. The classification of HAH manuscripts is performed in several steps. First, the HAH manuscript's image is segmented into words, and then each word is segmented into its connected parts. Due to the existing overlap between the adjacent connected parts of a single word, we developed a stretching algorithm to increase the gap between them and thus improve their segmentation. Second, several structural and statistical features, which are devised for Arabic text, are extracted from these connected parts and then combined to represent a word with one consolidated feature vector. Finally, a neural network is used to learn and classify the input vectors into word classes. These classes are then utilized to retrieve HAH manuscripts. The extraction of structural and statistical features from the individual connected parts, as compared to the extraction of these features from the whole word, improved the performance of the system significantly.