Handwritten Arabic Documents Indexation using HOG Feature

Abstract

See, stats, and : https : / / www . researchgate . net / publication / 281909964 Handwritten using Article DOI : 10 . 5120 / ijca2015906182 CITATION 1 READS 74 4 , including : Some : detection Medical Youssef Université 7 SEE Khaissidi ENSA 15 SEE Mostafa Université 35 SEE All. The . ABSTRACT The old manuscripts are a part of the richest cultural heritage and legacy of civilizations where the digitalization is a solution for the preservation of these manuscripts . The conception of handwriting recognition system knows today a great expansion and appears as a necessity in order to exploit the wealth of information contained in ancient manuscripts . In this paper , a holistic approach for spotting and searching query , especially , for images documents in handwritten Arabic is proposed . These operations need a lot of time and effort to do manual work . For this , we use in the first time text line segmentation of handwritten document image based on partial projection , where a sliding - window approach is used to locate the document regions that are most similar to the query . Histograms of Oriented Gradients (HOGs) are used as the feature vectors to represent the query and documents image , then Support Vector Machines (SVM) is used to produce a better representation of the query and to classify feature vectors . Finally , the application of the reclassification technique at the indexation stage , leads to better results .