Page 46 - programme book

AM-012
Robustness of Image Watermarking Scheme Based on Modified Non-
Separable Haar Wavelet Transform against Image Processing and
Geometric Attacks

Muhammad Khairi Abdul Razak 1, a) , Kamilah Abdullah 1, b) and Suhaila Abd Halim 1, c)

1 Center of Mathematics Studies, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA,
40450 Shah Alam, Selangor, Malaysia.

a) Corresponding author: khairi.kyrie@gmail.com
b) kamilah@tmsk.uitm.edu.my
c) suhaila@tmsk.uitm.edu.my

Abstract. Online communication has been made simple with the introduction of the Internet, so there
is a need to give protection to digital media. As technology continues to grow, more ways to use or
modify data are discovered. Accordingly, the protection of digital media also needs to continue to
develop. This paper presents a new non-blind image watermarking algorithm applying modified non-
separable Haar wavelet transform (NSHWT), singular value decomposition (SVD), Arnold’s cat map
and Rabin-p cryptosystem. The discrete wavelet transform (DWT) remains a highly popular choice
for transform domain image watermarking because of its useful properties. Even so, transform domain
watermarking can be resource-consuming, especially when dealing with larger data. To improve on
this, the proposed algorithm applies the modified NSHWT, which is a much more efficient method to
apply the DWT technique on an image. The embedded watermark image is protected by scrambling
the image using Arnold’s cat map, and the scrambling parameters are encrypted with the Rabin-p
cryptosystem. In general, the application of modified NSHWT and SVD makes the watermark highly
robust, and its security is ensured with the protection by Arnold’s cat map and Rabin-p cryptosystem.
The algorithm shows high robustness when under different image processing and geometric attacks.

Keywords: digital image watermarking, cryptosystem, robustness, NSHWT, SVD

AM-013
Application of Intuitionistic Type II Fuzzy Set on fEEG Image

Suzelawati Zenian 1,a) and Norhafiza Hamzah 1,b)

1 Mathematics Computer Graphics Programme, Faculty of Science and Natural Resources, Universiti Malaysia
Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.

a) Corresponding author: suzela@ums.edu.my
b) hafiza@ums.edu.my

Abstract. In this paper, the fEEG images are enhanced based on an intuitionistic type II fuzzy set. The
non-membership function is defined by a Sugeno type intuitionistic fuzzy generator. Moreover, a new
membership function is defined by using Hamacher t-conorm. Experimental results show that the
method provides better results compared to classical methods.

Keywords: fEEG image, type II fuzzy set, intuitionistic fuzzy set, image enhancement

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