An LBP encoding scheme jointly using quaternionic representation and angular information
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Local descriptors play a crucial role in numerous computer vision and pattern recognition applications. This paper proposes a novel local descriptor, called the quaternionic local angular binary pattern (QLABP), for color image classification. QLABP is based on the quaternionic representation (QR) of color images such that it is able to handle all color components holistically as well as consider their relations. Using QR, the quaternionic angular information is further developed to account for more color characteristics. We provide two ways to derive the quaternionic angular information from different perspectives. A pattern encoding operation is finally conducted on the obtained angular information to obtain QLABP. The effectiveness of QLABP has successfully been evaluated by comparing with several state-of-the-art descriptors.
KeywordsQuaternionic representation (QR) Local binary pattern (LBP) Quaternionic angular information Image classification
This work was partially supported by the National Natural Science Foundation of China (Nos. 61702129, 61772149, U1701267, and 61320106008), China Postdoctoral Science Foundation (No. 2018M633047), Guangxi Science and Technology Project (No. 2018AD19029), the Macau Science and Technology Development Fund under Grant FDCT/189/2017/A3, and by the Research Committee at University of Macau under Grants MYRG2016-00123-FST and MYRG2018-00136-FST.
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Conflict of interest
The authors declare that they have no conflict of interest.
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