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An Analysis of Colour Semantics in Art Images

Ivanova, Krassimira — 2012

Serdica Journal of Computing

This article presents the principal results of the Ph.D. thesis A Novel Method for Content-Based Image Retrieval in Art Image Collections Utilizing Colour Semantics by Krassimira Ivanova (Institute of Mathematics and Informatics, BAS), successfully defended at Hasselt Uni-versity in Belgium, Faculty of Science, on 15 November 2011. The article briefly presents the results achieved by the PhD project R-1875 “Search in Art Image Collections Based on Colour Semantics”, Hasselt University,...

Analysis of the Distributions of Color Characteristics in Art Painting Images

Ivanova, KrassimiraStanchev, PeterDimitrov, Boyan — 2008

Serdica Journal of Computing

In this paper we study some of the characteristics of the art painting image color semantics. We analyze the color features of differ- ent artists and art movements. The analysis includes exploration of hue, saturation and luminance. We also use quartile’s analysis to obtain the dis- tribution of the dispersion of defined groups of paintings and measure the degree of purity for these groups. A special software system “Art Paint- ing Image Color Semantics” (APICSS) for image analysis and retrieval...

Classifier PGN: Classification with High Confidence Rules

Mitov, IliyaDepaire, BenoitIvanova, KrassimiraVanhoof, Koen — 2013

Serdica Journal of Computing

ACM Computing Classification System (1998): H.2.8, H.3.3. Associative classifiers use a set of class association rules, generated from a given training set, to classify new instances. Typically, these techniques set a minimal support to make a first selection of appropriate rules and discriminate subsequently between high and low quality rules by means of a quality measure such as confidence. As a result, the final set of class association rules have a support equal or greater than a...

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