Segmentation and analysis of handwritten scripts from patients with neurological diseases
CompSysTech '03 Proceedings of the 4th international conference conference on Computer systems and technologies: e-Learning
A Method for Character String Extraction Using Local and Global Segment Crowdedness
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Text line detection in handwritten documents
Pattern Recognition
Automatic Evaluation of Stroke Slope
Biometrics and Identity Management
A hybrid method for three segmentation level of handwritten Arabic script
Proceedings of the International Workshop on Multilingual OCR
Text line and word segmentation of handwritten documents
Pattern Recognition
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
A new scheme for unconstrained handwritten text-line segmentation
Pattern Recognition
Automatic indexing of French handwritten census registers for probate geneaology
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Text line segmentation for gray scale historical document images
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Natural language inspired approach for handwritten text line detection in legacy documents
LaTeCH '12 Proceedings of the 6th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities
Text line extraction for historical document images
Pattern Recognition Letters
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The method herein proposed detects text lines on handwritten pages which may include either lines oriented in several directions, erasures, or annotations between main lines. The method has a hypothesis-validation strategy which is iteratively activated until the end of the segmentation is reached. At each stage of the process, the best text-line hypothesis is generated in the Hough domain. Taking into account the fluctuations of the text-line components. Afterwards, the validity of the line is checked in the image domain using a proximity criteria which analyses the context in which is perceived the alignment hypothesized. Ambiguous components belonging to several text lines are also marked.