Abstract
This contribution improves content-based hash functions for image retrieval systems using nested lattice codes. Lattice codes are used to quantize image feature vectors to final hash values. The goal is to develop a nested lattice indexing scheme such that there is a proportional relationship between Euclidean distance and some metric distances (Hamming distance or, as in this paper, weighted Hamming distance and first difference distance) in order to increase the hash function’s robustness. The proposed two-dimensional nested lattice code reduces the normalized mean squared error (NMSE) by 20 % compared to two-dimensional Gray code.
Keywords
B.M. Kurkoski—This work was supported by JSPS Kakenhi Grant Number 26289119.
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Nguyen, T.X., Hernandez, R.A.P., Kurkoski, B.M. (2016). Robust Content-Based Image Hash Functions Using Nested Lattice Codes. In: Shi, YQ., Kim, H., Pérez-González, F., Echizen, I. (eds) Digital-Forensics and Watermarking. IWDW 2015. Lecture Notes in Computer Science(), vol 9569. Springer, Cham. https://doi.org/10.1007/978-3-319-31960-5_33
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DOI: https://doi.org/10.1007/978-3-319-31960-5_33
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