원문정보
초록
영어
Automatic off-line Arabic handwriting recognition still faces a big challenges. Due to the cursive nature of the Arabic language, most of published works are based on recognition of a whole word without segmentation. This paper presents a new framework for the recognition of handwritten Arabic words based on segmentation. This framework involves two phases (training phase and testing phase). In the training phase, Arabic handwritten characters were trained to be recognized, while in the testing phase, words were segmented into characters for recognition. Classification is achieved in two steps (classification of the segmented characters and classification of the word). A dictionary is constructed and used to correct any errors occurring during the previous stages of the recognition process. This work has been tested with IFN/ENIT database and a comparison made against some existing methods and promising results have been obtained.
목차
1. Introduction
2. Challenges and Motivation
3. A Framework based on Segmentation
3.1. Training Phase
3.2. Testing Phase
4. Experimental Results
4.1. Segmentation of the Word into Characters
4.2. Classification of the Segmented Characters
4.3. Classification of Words
5. Conclusion and Future Work
References
저자정보
참고문헌
- 1(Reference title not available)
- 2(Reference title not available)
- 3Off-Line Arabic Handwritten Word Segmentation Using Rotational Invariant Segments Features.네이버 원문 이동
- 4Segmentation of Arabic Handwriting Based on both Contour and Skeleton Segmentation네이버 원문 이동
- 5Arabic handwriting recognition: Challenges and solutions네이버 원문 이동
- 6(Reference title not available)
- 7(Reference title not available)
- 8(Reference title not available)
- 9A new approach for off-line handwritten Arabic word recognition using KNN classifier네이버 원문 이동
- 10A comparative study between methods of Arabic baseline detection네이버 원문 이동