A Baseline Dependent Approach for Persian Handwritten Character Segmentation

-- In this paper, an efficient approach to segment Persian off-line handwritten text-line into characters is presented. The proposed algorithm first traces the baseline of the input text-line image and straightens it. Subsequently, it over-segments each word/subwords using features extracted from histogram analysis and then removes extra segmentation points using some baseline dependent as well as language dependent rules. We tested the proposed character segmentation scheme with 2 different datasets. On a test set of 899 Persian words/subwords created by us, 90.26% of the characters were segmented correctly. From another dataset of 200 handwritten Arabic word images [11] we obtained 93.49% correct segmentation accuracy. Keywords-Persian handwritten character recognition; Character segmentation; Baseline alignment; Projection analysis.

• Type: Journal
• Year: 2010
• Where: ICPR
• Authors: Alireza Alaei, P. Nagabhushan, Umapada Pal
• Keywords: Character Segmentation, Character Segmentation Scheme, Computer Vision, ICPR 2010, Off-line Handwritten Text-line