
Proceedings Paper
Local binary pattern based on image gradient for bark image classificationFormat | Member Price | Non-Member Price |
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Paper Abstract
In this work, we present a discriminative and effective local texture descriptor for bark image classification. The proposed descriptor is based on three factors, namely, pixel, magnitude and direction value. Unlike most other descriptors based on original local binary pattern, the proposed descriptor is conducted the changing of local texture of bark image. The performance of the proposed descriptor is evaluated on three benchmark datasets. The experimental results show that our approach is highly effective.
Paper Details
Date Published: 17 April 2019
PDF: 6 pages
Proc. SPIE 11071, Tenth International Conference on Signal Processing Systems, 110710P (17 April 2019); doi: 10.1117/12.2522093
Published in SPIE Proceedings Vol. 11071:
Tenth International Conference on Signal Processing Systems
Kezhi Mao; Xudong Jiang, Editor(s)
PDF: 6 pages
Proc. SPIE 11071, Tenth International Conference on Signal Processing Systems, 110710P (17 April 2019); doi: 10.1117/12.2522093
Show Author Affiliations
Tuan Le-Viet, Ho Chi Minh City Open Univ. (Viet Nam)
Vinh Truong Hoang, Ho Chi Minh City Open Univ. (Viet Nam)
Published in SPIE Proceedings Vol. 11071:
Tenth International Conference on Signal Processing Systems
Kezhi Mao; Xudong Jiang, Editor(s)
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