The logical style painting classifier based on Horn clauses and explanations (ℓ-SHE)Download PDFOpen Website

Published: 01 Jan 2021, Last Modified: 04 Mar 2024Log. J. IGPL 2021Readers: Everyone
Abstract: This paper presents a logical Style painting classifier based on evaluated Horn clauses, qualitative colour descriptors and Explanations (⁠|$\ell $|-SHE). Three versions of |$\ell $|-SHE are defined, using rational Pavelka logic (RPL), and expansions of Gödel logic and product logic with rational constants: RPL, |$G(\mathbb{Q})$| and |$\sqcap (\mathbb{Q})$|⁠, respectively. We introduce a fuzzy representation of the more representative colour traits for the Baroque, the Impressionism and the Post-Impressionism art styles. The |$\ell $|-SHE algorithm has been implemented in Swi-Prolog and tested on 90 paintings of the QArt-Dataset and on 247 paintings of the Paintings-91-PIB dataset. The percentages of accuracy obtained in the QArt-Dataset for each |$\ell $|-SHE version are 73.3% (RPL), 65.6% (⁠|$G(\mathbb{Q})$|⁠) and 68.9% (⁠|$\sqcap (\mathbb{Q})$|⁠). Regarding the Paintings-91-PIB dataset, the percentages of accuracy obtained for each |$\ell $|-SHE version are 60.2% (RPL), 48.2% (⁠|$G(\mathbb{Q})$|⁠) and 57.0% ( |$\sqcap (\mathbb{Q})$|⁠). Our logic definition for the Baroque style has obtained the highest accuracy in both datasets, for all the |$\ell $|-SHE versions (the lowest Baroque case gets 85.6|$\%$| of accuracy). An important feature of the classifier is that it provides reasons regarding why a painting belongs to a certain style. The classifier also provides reasons about why outliers of one art style may belong to another art style, giving a second classification option depending on its membership degrees to these styles.
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