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Open AccessArticle

Image-Level Structure Recognition Using Image Features, Templates, and Ensemble of Classifiers

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Department of Computer Engineering, Eastern Mediterranean University, 99628 Gazimagusa, TRNC, Mersin 10, Turkey
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Department of Electrical & Electronics Engineering, Eastern Mediterranean University, 99628 Gazimagusa, TRNC, Mersin 10, Turkey
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Author to whom correspondence should be addressed.
Symmetry 2020, 12(7), 1072; https://doi.org/10.3390/sym12071072
Received: 12 May 2020 / Revised: 13 June 2020 / Accepted: 23 June 2020 / Published: 30 June 2020
Image-level structural recognition is an important problem for many applications of computer vision such as autonomous vehicle control, scene understanding, and 3D TV. A novel method, using image features extracted by exploiting predefined templates, each associated with individual classifier, is proposed. The template that reflects the symmetric structure consisting of a number of components represents a stage—a rough structure of an image geometry. The following image features are used: a histogram of oriented gradient (HOG) features showing the overall object shape, colors representing scene information, the parameters of the Weibull distribution features, reflecting relations between image statistics and scene structure, and local binary pattern (LBP) and entropy (E) values representing texture and scene depth information. Each of the individual classifiers learns a discriminative model and their outcomes are fused together using sum rule for recognizing the global structure of an image. The proposed method achieves an 86.25% recognition accuracy on the stage dataset and a 92.58% recognition rate on the 15-scene dataset, both of which are significantly higher than the other state-of-the-art methods. View Full-Text
Keywords: ensemble of classifiers; image features; predefined templates; stage recognition; 3D scene geometry ensemble of classifiers; image features; predefined templates; stage recognition; 3D scene geometry
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Khan, A.; Chefranov, A.; Demirel, H. Image-Level Structure Recognition Using Image Features, Templates, and Ensemble of Classifiers. Symmetry 2020, 12, 1072.

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