Keyword-guided Arabic word spotting in ancient document images using Curvelet descriptors

This paper deals with the contribution of Curvelet transform to generate more accurate word image descriptors for Arabic keyword spotting in ancient documents. Due to its properties, Curvelets can tolerate more scale distortions and more directional features in images. The process of Curvelet descriptor generation is applied to each word image in the dataset. Therefore, dynamic time warping algorithm is employed to match corresponding coefficients from Curvelet descriptor matrices. Experimental results on ancient Arabic document demonstrate that the characterization of the word image from the Curvelet descriptors offers better performance comparatively to the major state-of-the-art word image descriptors.