A New Bilinear Supervised Neighborhood Discrete Discriminant Hashing

Xueyu Chen, Minghua Wan, Hao Zheng, Chao Xu, Chengli Sun and Zizhu Fan
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Xueyu Chen: School of Information Engineering, Nanjing Audit University, Nanjing 211815, China
Minghua Wan: School of Information Engineering, Nanjing Audit University, Nanjing 211815, China
Hao Zheng: Key Laboratory of Intelligent Information processing, Nanjing Xiaozhuang University, Nanjing 211171, China
Chao Xu: School of Information Engineering, Nanjing Audit University, Nanjing 211815, China
Chengli Sun: School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China
Zizhu Fan: School of Science, East China Jiaotong University, Nanchang 330013, China

Mathematics, 2022, vol. 10, issue 12, 1-18

Abstract: Feature extraction is an important part of perceptual hashing. How to compress the robust features of images into hash codes has become a hot research topic. Converting a two-dimensional image into a one-dimensional descriptor requires a higher computational cost and is not optimal. In order to maintain the internal feature structure of the original two-dimensional image, a new Bilinear Supervised Neighborhood Discrete Discriminant Hashing (BNDDH) algorithm is proposed in this paper. Firstly, the algorithm constructs two new neighborhood graphs to maintain the geometric relationship between samples and reduces the quantization loss by directly constraining the hash codes. Secondly, two small rotation matrices are used to realize the bilinear projection of the two-dimensional descriptor. Finally, the experiment verifies the performance of the BNDDH algorithm under different feature types, such as image original pixels and a Convolutional Neural Network (CNN)-based AlexConv5 feature. The experimental results and discussion clearly show that the proposed BNDDH algorithm is better than the existing traditional hashing algorithm and can represent the image more efficiently in this paper.

Keywords: feature extraction; perceptual hashing; discrete optimization; bilinear projection; neighborhood relationship (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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