Impact of a Codebook Filtering Step on a Galois Lattice Structure for Graphics Recognition

Ameni Boumaiza (1) , Salvatore Tabbone (1)

1 QGAR - Querying Graphics through Analysis and Recognition

In this paper, we propose an evaluation of the impact of a codebook filtering step on the recognition rate of a Galois lattice classifier. Unlike the usual approach which only considers a whole visual dictionary and is likely to over-fitting, we boost the Galois lattice using a filtered dictionary by assigning a probability of appearance to each visual word in a symbol model. The retrieval performance and behavior of the method have been compared to state-of-the art and proved that is suitable to the recognition process. Experimental results show that the Galois Lattice classifier combined with a filtered codebook outperforms classic classifiers. Interestingly, due to the high selection of features from the dictionary, the accuracy improvement is obtained with a considerable computational cost reduction.

Mots clés: Galois lattice; Bag od words; Frequent itemsets; Classification

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]; Apprentissage [cs.LG]; Traitement du texte et du document; Vision par ordinateur et reconnaissance de formes [cs.CV]

Ameni Boumaiza, Salvatore Tabbone. Impact of a Codebook Filtering Step on a Galois Lattice Structure for Graphics Recognition. 21st International Conference on Pattern Recognition, Nov 2012, Tsukuba International Congress Center, Japan. pp.4. ⟨hal-00759516⟩