KERTAS: dataset for automated relationship of ancient manuscripts that are arabic

KERTAS: dataset for automated relationship of ancient manuscripts that are arabic

Abstract

The chronilogical age of a historic manuscript can be a great supply of information for paleographers and historians. The entire process of automated manuscript age detection has complexities that are inherent that are compounded by the not enough suitable datasets for algorithm assessment. This paper presents a dataset of historic handwritten Arabic manuscripts created particularly to check advanced age and authorship detection algorithms. Qatar nationwide Library happens to be the source that is main of with this dataset as the staying manuscripts are available supply. The dataset comes with over pictures obtained from various handwritten Arabic manuscripts spanning fourteen hundreds of years. In addition, a sparse approach that is representation-based dating historical Arabic manuscript normally proposed. There clearly was not enough current datasets that offer dependable writing date and writer identity as metadata. KERTAS is a dataset that is new of papers that will help scientists, historians and paleographers to immediately date Arabic manuscripts more accurately and effectively.

Introduction

Islamic civilization contributed notably to contemporary civilization; the time through the 8th to 14th century is recognized as the Islamic golden chronilogical age of knowledge.