@inproceedings{de4b13e69241461c978cdddc34b2d5c3,
title = "Generalized local N-ary patterns for texture classification",
abstract = "Local Binary Pattern (LBP) has been well recognised and widely used in various texture analysis applications of computer vision and image processing. It integrates properties of texture structural and statistical texture analysis. LBP is invariant to monotonic gray-scale variations and has also extensions to rotation invariant texture analysis. In recent years, various improvements have been achieved based on LBP. One of extensive developments was replacing binary representation with ternary representation and proposed Local Ternary Pattern (LTP). This paper further generalises the local pattern representation by formulating it as a generalised weight problem of Bachet de Meziriac and proposes Local N-ary Pattern (LNP). The encouraging performance is achieved based on three benchmark datasets when compared with its predecessors.",
author = "Sheng Wang and Xiangjian He and Qiang Wu and Jie Yang",
year = "2013",
doi = "10.1109/AVSS.2013.6636660",
language = "English",
isbn = "9781479907038",
series = "2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013",
publisher = "IEEE Computer Society",
pages = "324--329",
booktitle = "2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013",
address = "United States",
note = "2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013 ; Conference date: 27-08-2013 Through 30-08-2013",
}