Locally baseline detection for online Arabic script based languages character recognition

Baseline detection is one of the most important step in character recognition and has direct influence on recognition result. Due to the complexity of the Urdu scripts based languages, handwritten character recognition is a very difficult task as compared to other languages. Baseline detection is one of the main issue and basic step of mostly preprocessing operations that is, normalization, skewness, secondary strokes segmentation and also in feature extraction. This paper presents a novel method of baseline detection for cursive handwritten Urdu script. The proposed approach is divided into three steps: diacritical marks segmentation, primary baseline estimation and local baseline estimation. The local baseline extraction is estimated using the features extracted from ending shape of the words. Due to structural difference between Nasta'liq and Naskh style, different rules are formed for baseline estimation.