Vignette detection and reconstruction of composed ornaments with a strengthened autoencoder

Mohammad Sadil Khan (1) , Rémi Emonet (1) , Thierry Fournel (1)

1 LHC - Laboratoire Hubert Curien

A strengthened autoencoder formed by placing an object detector upstream of a decoder is here developed in the context of the model-helped human analysis of composed ornaments from a dictionary of vignettes. The detection part is in charge to detect regions of interest containing some vignette features, and the decoding part to ensure vignette reconstruction with a relative quality depending on feature match. Images of ornaments without typographical composition are generated in order to properly assess the performance of each of the two parts.

Domaines: Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Mohammad Sadil Khan, Rémi Emonet, Thierry Fournel. Vignette detection and reconstruction of composed ornaments with a strengthened autoencoder. 2021. ⟨hal-03409930⟩