Development of Pose Estimation Algorithm for Quranic Arabic Word

Abstract

The study carried out in this report proposes the best keypoint detection, description, and pose estimation algorithm combination for Quranic Arabic words. Oriented-FAST Rotated-BRIEF (ORB) and Accelerated-KAZE (AKAZE) are used as the keypoint detection and description algorithms while Random Sample Consensus (RANSAC) and Least Median Squares (LMEDS) are used to evaluate the homography for pose estimation algorithms. The algorithms are combined with each other to provide four different techniques to estimate the pose of Quranic Arabic words. The algorithms are tested on a limited dataset chosen from a phrase within the Quran. Performance of each algorithm is measured in real-time through inlier to keypoint ratio which determines pose accuracy.

Framework of diacritic segmentation for Arabic handwritten document

“…To put this into example, in order the writer wants to master the Arabic script writing style, he/she should initially master the writing and right placement of the diacritics as well, in order to compose a right and surely knew Arabic [7]. Additionally, Mushaf Al-Quran is the heavenly and most fast approaching book for many Muslims around the globe [8]. It tends to contain two forms printed or digital form, though it's in Arabic, but its written in the way that is dissimilar from any Arabic/Jawi document based as it encompasses "Diacritics" [9], [10].…”