Verification of Hierarchical Classifier Results for Handwritten Arabic Word Spotting

Large amounts of handwritten documents have been digitized, and the need to search and index these documents is increasing to make them more accessible. Different word spotting systems have been proposed to search for words for this purpose. Since the precision of the word spotting system is crucial, verifying the results of a word spotting system is becoming an effective approach to improve the system performance. In this paper, we propose two verification models for Arabic word spotting systems. Both models make use of a holistic classifier. The first model is based on matching the results of the word spotting system with those of the holistic classifier, while the other model derives a new score evaluation based on the two results. Verifying a word spotting system using these models can significantly improve its performance, since the precision rate increased from 74% to 77.7% and 84.4% respectively with the Word Matching and Score Evaluation models of verification, at 50% recall.