Title :
Segmentation and Recognition Strategy of Handwritten Connected Digits Based on the Oriented Sliding Window
Author :
Gattal, Abdeljalil ; Chibani, Youcef
Author_Institution :
Univ. de Tebessa, Tebessa, Algeria
Abstract :
In this paper, we propose a system to recognize handwritten digit strings, which constitutes a difficult task because of overlapping and/or joining of adjacent digits. To resolve this problem, we use a segmentation-recognition of handwritten connected digits based on the oriented sliding window. The proposed approach allows separating adjacent digits according the connection configuration by finding at the same time the interconnection points between adjacent digits and the cutting path. The segmentation-recognition using the global decision module allows the rejection or acceptance of the processed image. Experimental results conducted on the handwritten digit database NIST SD19 show the effective use of the sliding window for segmentation-recognition.
Keywords :
document image processing; handwritten character recognition; image segmentation; adjacent digit; connection configuration; cutting path; global decision module; handwritten connected digits; handwritten digit strings; interconnection point; oriented sliding window; recognition strategy; segmentation strategy; Databases; Handwriting recognition; IP networks; Image segmentation; NIST; Skeleton; handwritten digits; oriented sliding window; segmentation; segmentation-recognition;
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on
Conference_Location :
Bari
Print_ISBN :
978-1-4673-2262-1
DOI :
10.1109/ICFHR.2012.265