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Proceedings Paper

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern
Author(s): Qian Gong; Zhiyi Qu; Kun Hao
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Paper Abstract

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

Paper Details

Date Published: 21 July 2017
PDF: 6 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200G (21 July 2017); doi: 10.1117/12.2281706
Show Author Affiliations
Qian Gong, Lanzhou Univ. (China)
Zhiyi Qu, Lanzhou Univ. (China)
Kun Hao, Lanzhou Univ. (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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