01201nas a2200277   4500000000100000000000100001008004100002260001200043653001900055653002200074653000800096653002100104653001800125100002300143700002000166700001900186700002400205700001900229700001900248245006900267856009800336300000900434490000600443520046000449022001400909       2016                            d  c09/201610aClassification10aImage Recognition10aHOG10aArabic Documents10aWord Spotting1 aGhizlane Khaissidi1 aYoussef Elfakir1 aMostafa Mrabti1 aMounîm El Yacoubi1 aDriss Chenouni1 aZakia Lakhliai00aSegmentation-free Word Spotting for Handwritten Arabic Documents  uhttp://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_1_pdf_95245.pdf  a6-100 v43 aIn this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs) are used as the feature vectors to represent the query and documents image. Then, we compress the descriptors with the product quantization method. Finally, a better representation of the query is obtained by using the Support Vector Machines (SVM).  a1989-1660