Seok-Tae Kim

Integral Imaging Based 3-D Image Encryption Algorithm Combined with Cellular Automata

A novel optical encryption method is proposed in this paper to achieve 3-D image encryption. This proposed encryption algorithm combines the use of computational integral imaging (CII) and linear-complemented maximum- length cellular automata (LC-MLCA) to encrypt a 3D image. In the encryption process, the 2-D elemental image array (EIA) recorded by light rays of the 3-D image are mapped inversely through the lenslet array according the ray tracing theory. Next, the 2-D EIA is encrypted by LC-MLCA algorithm. When decrypting the encrypted image, the 2-D EIA is recovered by the LC-MLCA. Using the computational integral imaging reconstruction (CIIR) technique and a 3-D object is subsequently reconstructed on the output plane from the 2-D recovered EIA. Because the 2-D EIA is composed of a number of elemental images having their own perspectives of a 3-D image, even if the encrypted image is seriously harmed, the 3-D image can be successfully reconstructed only with partial data. To verify the usefulness of the proposed algorithm, we perform computational experiments and present the experimental results for various attacks. The experiments demonstrate that the proposed encryption method is valid and exhibits strong robustness and security.

Watermarking Based on Complemented MLCA and 2D CAT

Digital watermarking has gained importance in recent years in copyright protection and multimedia. This paper proposes a secure and novel watermarking system based on complemented Maximum Length Cellular Automata (MLCA) and Two-Dimension Cellular Automata Transform (2D CAT). In this watermarking scheme, the original watermark is first encrypted by complemented MLCA with the private keys, and then the encrypted watermark is embedded into the CAT domain of the cover image, at last use the inverse CAT for the transformed image, the watermarked image is obtained. Experiment results show that this new method is more secure and provides robust performance against watermarking attacks.

Copyright protection for elemental image array by hypercomplex Fourier transform and an adaptive texturized holographic algorithm

In practical applications of three-dimensional integral imaging, the captured elemental image array (EIA) needs to be stored and delivered through the Internet. Therefore, there is an urgent need for protecting the copyright of EIA against piracy and malicious manipulation. In our work, we propose a copyright protection algorithm for EIA by combining the use of the modified hypercomplex Fourier transform (HFT) and the adaptive texturized holographic algorithm. The modified HFT can accurately extract the features from each elemental image. According to these features, we embed watermark into the visually less noticeable regions of the EIA to increase the visual perception. In addition, an adaptive texturized holographic algorithm is proposed to increase the robustness. Finally, the analytical performances are contrasted with simulation results where the imperceptibility and robustness of the proposed method are evaluated against standard attacks.

A New Algorithm for Wavelet Watermarking Based on Linear Bit Expansion and Its Similarity Measurement

In this paper proposes a new wavelet watermark technique based on the linear bit expansion. To ensure the security of the watermark, enlarged watermark by applying linear bit expansion is inserted in a given intensity to a low frequency sub-band of the image which is wavelet transformed after the Arnold Transformation. Using F norm function to detect the presence of watermark is applied which is different from existing methods. The experimental results verify that the proposed watermarking technique has outstanding quality in regards to fidelity and robustness.

T -fuzzy semiautomata over finite groups

Abstract We introduce the concepts of T -fuzzy semiautomata and obtain some results concerning them.

Designing Three-Dimensional Cellular Automata Based Video Authentication With an Optical Integral Imaging Generated Memory-Distributed Watermark

Integral imaging for image watermarking is attracting a great deal of interest as it provides high processing speed and data redundancy property. Traditional video watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform and discrete wavelet transform. Most of these algorithms generally provide one transform plane for watermarking. In this paper, we propose a video watermarking by employing three-dimensional (3-D) cellular automata (CA) transform and perfect-reconstruction integral imaging (PRII). Compared to the existing works, the main strength of this paper is to utilize a 3-D CA transform to produce multiple transform planes for watermark embedding, so that greatly improve the security; decompose watermark into a series of elemental images using integral imaging to enhance the robustness; and employ perfect-reconstruction filter into the iterative back-projection process thus resolving the ringing artifacts problems. Experimental results show that the proposed PRII-based watermarking method outperforms other similar watermarking methods and is robust to a wide range of attacks, e.g., Gaussian noise, salt and pepper noise, frame clipping, JPEG compression, and median filter attack.

Generation of TPMACA for Pattern Classification

The important prerequisites of designing pattern classifier are high throughput and low cost hardware implementation. The simple, regular, modular and cascadable local neighborhood sparse network of Cellular Automata (CA) suits ideally for low cost VLSI implementation. Thus the multiple attractor CA is adapted for use as a pattern classifier. By concatenating two predecessor multiple attractor CA (TPMACA) we can construct a pattern classifier. In this paper we propose a method for finding dependency vector by using a 0-basic path. Also we propose various methods for generating TPMACA corresponding to a given dependency vector.

A Novel Image Encryption using Complemented MLCA based on NBCA and 2D CAT

In this paper, we propose encryption method to using complemented MLCA(Maximum Length Cellular Automata) based on NBCA(Null Boundary CA) and 2D CAT (Two-Dimensional Cellular Automata Transform) for efficient image encryption. The encryption method is processed in the following order. First, a transition matrix T is created using the Wolfram Rule matrix. Then, the transition matrix T is multiplied to the original image that is intended to be encrypted, which transfers the pixel values of the original image. Furthermore, the converted original image goes through a XOR operation with complemented vector F to convert into a complemented MLCA applied image. Then, the gateway value is set and 2D CAT basis function is created. Also, the 2D CAT is encrypted by multiplying the created basis function to the complemented MLCA applied image. Lastly, the stability analysis verifies that proposed method holds a high encryption quality status.

Nonlinear Pseudorandom Sequences Based on 90/150 LHGCA

In a stream cipher the plaintext digits are encrypted one at a time, and the transformation of successive digits varies during the encryption. LFSRs produce sequences having large periods and good statistical properties, and are readily analyzed using algebraic techniques. But the output sequences of LFSRs are also easily predictable, if we know proper successive output sequences in output sequences. In this paper, we give a new method which generates nonlinear sequences using maximum-length cellular automata.

Optical encryption via monospectral integral imaging

Optical integral imaging (II) uses a lenslet array and CCD sensor as the 3D acquisition device, in which the multispectral information is acquired by a color filter array (CFA). However, color crosstalk exists in CFA that diminishes color gamut, resulting in the reduced resolution. In this paper, we present a monospectral II encryption approach with a monospectral camera array (MCA). The monospectral II system captures images with the MCA that can eliminate color crosstalk among the adjacent spectral channels. It is noteworthy that the captured elemental images (EIs) from the colored scene belong to grayscale; the colored image encryption is converted to grayscale encryption. Consequently, this study will significantly save the calculation load in image encoding and decoding (nearly reduced 2/3) compared with the similar works. Afterwards, an optimized super-resolution reconstruction algorithm is introduced to improve the viewing resolution.