Combining visual and textual features for indexing images: a hybrid approach


  • Ali Benafia
  • Ramdane Maamri University of Constantine, Constantine-Algeria
  • Zaidi Sahnoun University of Constantine, Constantine,Algeria
  • Chaouki Babahenini University of Biskra, Biskra


complex term extraction, linguistic analysis, syntactic patterns, textual features, visual features


In this paper, we propose a new hybrid approach for indexing images and retrieving images from a corpus of images .The proposed approach is based on the fusion of the low level visual and textual descriptors. First, we describe each image of corpus in a model based on graphs. Then, in a second model, we translate the legends associated to images. These two models permit us to calculate the set of visual and textual descriptors for global index .We uses heuristics for the calculation of these features. The proposed approach is tested on a set of images and the results are compared with the human expert indexing.


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Benafia, A. ., Maamri, R., Sahnoun, Z. ., & Babahenini, C. . (2020). Combining visual and textual features for indexing images: a hybrid approach. International Journal on Information Technology and Computer Science, 4(2). Retrieved from



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