01529nas a2200229   4500000000100000000000100001008004100002260001200043653002100055653003800076653002700114653002300141653001700164100002200181700001400203245008100217856009700298300001000395490000600405520087400411022001401285       2019                            d  c06/201910aArabic Documents10aHandwritten Character Recognition10aText Line Segmentation10aProjection Profile10aSeam Carving1 aAbdelghani Souhar1 aM Daldali00aHandwritten Arabic Documents Segmentation into Text Lines using Seam Carving  uhttps://www.ijimai.org/journal/sites/default/files/files/2018/06/ijimai_5_5_11_pdf_12351.pdf  a89-960 v53 aInspired from human perception and common text documents characteristics based on readability constraints, an Arabic text line segmentation approach is proposed using seam carving. Taking the gray scale of the image as input data, this technique offers better results at extracting handwritten text lines without the need for the binary representation of the document image. In addition to its fast processing time, its versatility permits to process a multitude of document types, especially documents presenting low text-to-background contrast such as degraded historical manuscripts or complex writing styles like cursive handwriting. Even if our focus in this paper was on Arabic text segmentation, this method is language independent. Tests on a public database of 123 handwritten Arabic documents showed a line detection rate of 97.5% for a matching score of 90%.  a1989-1660