Abstract
In this paper, a new class of image texture operators is proposed. We firstly determine that the number of gray levels in each B × B subblock is a fundamental property of the local image texture. Thus, an occurrence histogram for each B × B sub-block can be utilized to describe the texture of the image. Moreover, using a new multi-bit plane strategy, i.e., representing the image texture with the occurrence histogram of the first one or more significant bit-planes of the input image, more powerful operators for describing the image texture can be obtained. The proposed approach is invariant to gray scale variations since the operators are, by definition, invariant under any monotonic transformation of the gray scale, and robust to rotation. They can also be used as supplementary operators to local binary patterns (LBP) to improve their capability to resist illuminance variation, surface transformations, etc.
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Fangjun Huang received the B.S. degree from Nanjing University of Science and Technology, China, in 1995, and the M.S. and Ph.D. degrees from Huazhong University of Science and Technology, China, in 2002 and 2005, respectively. From June 2009 to June 2010, he was a postdoctoral researcher in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology. From September 2013 to August 2014, He was a Korea Foundation for Advanced Studies (KFAS) scholar in Korea University. He is currently an associate professor with the School of Information Science and Technology, Sun Yat-sen University, China. His research interests include multimedia security and image processing.
Xiaochao Qu received his B.S. degree in computer science and technology from Harbin Institute of Technology, China, in 2009. He is currently pursuing a Ph.D. degree in Korea University. His research interests are reversible watermarking, image processing, and pattern recognition.
Hyoung Joong Kim got the B.S. in electrical engineering in 1978, and M.S. and Ph.D. degrees in control and instrumentation engineering in 1986 and 1989, respectively, from Seoul National University. He was a visiting scholar from 1992 to 1993 at the University of Southern California, USA. He was a professor of Control and Instrumentation Engineering Department of Kangwon National University, Chuncheon, R. O. Korea, from 1989 to 2006. He is currently a professor of Korea University, R. O. Korea. His research interests include distributed computing, machine learning, and multimedia security.
Jiwu Huang received his B.S. degree from Xidian University, China, in 1982, M.S. degree from Tsinghua University, China, in 1987, and Ph.D. degree from the Institute of Automation, Chinese Academy of Sciences, China, in 1998. He is currently a professor with the College of Information Engineering (also Shenzhen Key Laboratory of Media Security), Shenzhen University, China. His current research interests include multimedia forensics and security. He serves as an associate editor for IEEE Transactions on Information Forensics and Security, and he also serves as a member of the IEEE SPS Information Forensics and Security Technical Committee.
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Huang, F., Qu, X., Kim, H.J. et al. Local pixel patterns. Comp. Visual Media 1, 157–170 (2015). https://doi.org/10.1007/s41095-015-0014-4
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DOI: https://doi.org/10.1007/s41095-015-0014-4