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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
using feature vector. We do static analysis over computed features to get distinguishing feature descriptors. Maximum similarity i.e. minimum distance allows us to find the query relevant combined pictures and associated relevant words. For textual part of the query we compute the concepts (keywords as well as synonyms of
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