caa a22 4500 605469288 CHVBK 20210128100321.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00500-014-1323-8 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1323-8 Cyganek Bogusław AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland aut Hybrid ensemble of classifiers for logo and trademark symbols recognition [Elektronische Daten] [Bogusław Cyganek] The paper presents a hybrid ensemble of diverse classifiers for logo and trademark symbols recognition. The proposed ensemble is composed of four types of different member classifiers. The first one compares color distribution of the logo patterns and is responsible for sifting out images of different color distribution. The second of the classifiers is based on the structural tensor recognition of local phase histograms. A proposed modification in this module consists of tensor computation in the space of the morphological scale-space. Thanks to this, more discriminative histograms describing global shapes are obtained. Next in the chain, is a novel member classifier that joins the Hausdorff distance with the correspondence measure of the log-polar patches computed around the corner points. This sparse classifier allows reliable comparison of even highly deformed patterns. The last member classifier relies on the statistical affine moment invariants which describe global shapes. However, a real advantage is obtained by joining the aforementioned base classifiers into a hybrid ensemble of classifiers, as proposed in this paper. Thanks to this a more accurate response and generalizing properties are obtained at reasonable computational requirements. Experimental results show good recognition accuracy even for the highly deformed logo patterns, as well as fair generalization properties which support human search and logo assessment tasks. Springer-Verlag Berlin Heidelberg, 2014 Logo recognition nationallicence Trademark classification nationallicence Structural tensor nationallicence Modified Hausdorff distance nationallicence Fuzzy image measures nationallicence Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3413-3430 1432-7643 19:12<3413 2015 19 500 https://doi.org/10.1007/s00500-014-1323-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1323-8 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Cyganek Bogusław AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3413-3430 1432-7643 19:12<3413 2015 19 500