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Abstract

Ahmed Fawzi, Moisés Pastor-i-Gadea, Carlos D. Martínez-Hinarejos. Baseline detection on Arabic Handwritten Documents. DocEng '17: Proceedings of the 2017 ACM Symposium on Document Engineering, 2017. pp. 193-196. ACM. ACM.

Document processing comprises different steps depending on the nature of the documents. For text documents, specially for handwritten documents, transcription of their contents is one of the main tasks. Handwritten Text Recognition (HTR) is the process of automatically obtaining the transcription of the content of a handwritten text document. In document processing, the basic unit for the acquisition process is the page image, whilst line image is the basic form for the HTR process. This is a bottle-neck which is holding back the massive industrial document processing. Baseline detection can be used not only to segment page images into line images but also for many other document processing steps. Baseline detection problem can be formulated as a clustering problem over a set of interest points. In this work, we study the use of an automatic baseline detection technique, based on interest point clustering, in Arabic handwritten documents. The experiments reveal that this technique provides promising results for this task.