Open AccessThe impact of the image processing in the indexation system
Author(s) -
Youssef Elfakir,
Ghizlane Khaissidi,
Gilles Despaux,
Driss Chenouni
Publication year - 2019
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v9i5.pp4311-4320
Subject(s) - computer science , scale invariant feature transform , codebook , artificial intelligence , curse of dimensionality , spotting , pattern recognition (psychology) , search engine indexing , indexation , word (group theory) , similarity (geometry) , image processing , image (mathematics) , mathematics , geometry , monetary economics , economics , monetary policy
This paper presents an efficient word spotting system applied to handwritten Arabic documents, where images are represented with bag-of-visual-SIFT descriptors and a sliding window approach is used to locate the regions that are most similar to the query by following the query-by-example paragon. First, a pre-processing step is used to produce a better representation of the most informative features. Secondly, a region-based framework is deployed to represent each local region by a bag-of-visual-SIFT descriptors. Afterward, some experiments are in order to demonstrate the codebook size influence on the efficiency of the system, by analyzing the curse of dimensionality curve. In the end, to measure the similarity score, a floating distance based on the descriptor’s number for each query is adopted. The experimental results prove the efficiency of the proposed processing steps in the word spotting system.