Title :
Recovery of drawing order in handwritten digit images
Author_Institution :
Center for Adv. Study in Math., Panjab Univ., Chandigarh, India
Abstract :
This paper presents recovery of drawing order that converts offline handwritten text to their online handwritten format. The offline text images are preprocessed using stages as size normalization, noise removal and thinning of text. We have proposed a traversal algorithm to recover drawing order of digit images that convert offline image to online handwriting format and find trajectory direction using chain code features. The chain code features are extracted from the recovered trajectories and support vector machine has used as recognition technique to recognize text images. Our approach has been implemented with MNIST database and we have achieved an overall error rate as 2.61%.
Keywords :
feature extraction; handwriting recognition; image thinning; support vector machines; MNIST database; chain code features; drawing order; feature extraction; handwritten digit images; noise removal; offline handwritten text; offline text images; online handwritten format; size normalization; support vector machine; text image recognition; text thinning; traversal algorithm; Conferences; Data preprocessing; Error analysis; Feature extraction; Information processing; Support vector machines; Trajectory; Offline handwriting; online handwriting; recovery of drawing order;
Conference_Titel :
Image Information Processing (ICIIP), 2013 IEEE Second International Conference on
Conference_Location :
Shimla
Print_ISBN :
978-1-4673-6099-9
DOI :
10.1109/ICIIP.2013.6707630