Efficient loose image content classifier

Huiqing Zhang; Luyu Sun; Ke Gu; Yutao Liu; Lijuan Tang

Efficient loose image content classifier

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Author(s): Huiqing Zhang¹ ; Luyu Sun¹ ; Ke Gu¹ ; Yutao Liu² ; Lijuan Tang³
- Affiliations: 1: Faculty of Information Technology , Beijing University of Technology , Beijing 100124 , People's Republic of China ;
  2: Graduate School at Shenzhen , Tsinghua University , People's Republic of China ;
  3: School of Information and Electronic , Jiangsu Vocational College of Business , People's Republic of China
Source: Volume 55, Issue 25, 12 December 2019, p. 1335 – 1337
DOI: 10.1049/el.2019.1636 , Print ISSN 0013-5194, Online ISSN 1350-911X

Received 10/09/2019, Published 24/10/2019

In this Letter, the authors put forward a loose classifier to determine whether the content of a given image belongs to screen content or natural scene. In the proposed classifier, they first extract 14 features by means of three typical histograms, the greyscale image histogram, local binary pattern histograms, and histograms of the oriented gradient, respectively. Then, in the second step, they try to build a non-linear mapping, with stacking-based integrated learners, from extracted features to the classification label. Experimental results prove that the effectiveness of their proposed method as compared with popular algorithms.

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