Cellular Automata Transform Research Articles

3D Copyright Protection Based on Binarized Computational Ghost Imaging Encryption and Cellular Automata Transform

In this paper, a watermark embedding scheme based on ghost image encryption and cellular automata transformation is proposed. In this scheme, the watermark forms speckle through different light intensities into a key, and the cellular automata transformation algorithm is embedded into the 3D image. Compared with the traditional watermarking encryption method, this scheme combines ghost imaging and the cellular automata transformation algorithm, which double guarantees and increases the confidentiality of the watermark. The binary computing ghost imaging discussed in this paper saves the storage space of password text and makes the transmission of password text more convenient and faster. Experiments on this method also verify that the watermark-embedded image has higher imperceptibility and higher robustness against attacks, and that the extracted watermark has good integrity.

Robust and Secure Video Watermarking Based on Cellular Automata and Singular Value Decomposition for Copyright Protection

In recent years, watermarking techniques have been under deliberation for their wide variety of applications in various fields. An organization transmits its data through digital communication channels, where the probability of attack is more. To protect the data transmitted through the channel, a novel fuzzy-based digital video watermarking scheme based on Cellular Automata Transform and Singular Value Decomposition (SVD) for copyright protection is proposed. The proposed scheme adopts a mixture of both cellular automata and SVD, which provides copyright protection with high robustness and imperceptibility for multiple transform planes with high processing speed and data redundancy. Moreover, the confidentiality of the proposed scheme is improved with the help of SVD. The watermarked video is experimented with to prove the strength by extracting the watermark image after applying geometric transformation, noise addition, enhancement, and compression attacks. The quantitative performance analysis, which shows improved robustness and imperceptibility of the proposed method compared to the existing methods, is performed by calculating the peak signal-to-noise ratio, structural similarity index, bit error rate, and normalized cross-correlation.

Fragile Watermarking based on Linear Cellular Automata using Manhattan Distances for 2D Vector Map

There has been a growing demand for publishing maps in secure digital format, since this ensures the integrity of data. This had lead us to put forward a method of detecting and locating modification data that is extremely accurate and simultaneously guarantees that the exact original content is recovered. More precisely, this method relies on a fragile watermarking algorithm that is developed in accordance with a frequency manner and, for every spatial feature, it can embed hidden data in 2D vector maps. The current paper proposes a frequency data-hiding scheme, which will be examined in accordance with Linear Cellular Automata Transform using Manhattan distances. Various invertible integer mappings are applied in order to find out the Manhattan distances from coordinates. To begin with, the original map is transformed into LCA, after which the watermark insertion process is carried out to transform the coefficient of the transformation result frequency into LSB. Lastly, a watermarked map is created by applying the inverse LCA transform, meaning that a LCA-transformed map is produced. Findings indicate that the suggested method is effective since in terms of invisibility and the capacity to allow for modifications. The methods also allow the detection of modification data, the addition and removal of some features, and enable the exact original content from the 2D vector map to be included.

Medical Image Watermarking Based on Visual Secret Sharing and Cellular Automata Transform for Copyright Protection

Medical Image Watermarking Based on Visual Secret Sharing and Cellular Automata Transform for Copyright Protection

Lossless medical image watermarking method based on significant difference of cellular automata transform coefficient

Conventional medical image watermarking techniques focus on improving invisibility and robustness of the watermarking mechanism to prevent medical disputes. This paper proposes a medical image watermarking algorithm based on the significant difference of cellular automata transform (CAT) for copyright protection. The medical image is firstly subsampled into four subimages, and two images are randomly chosen to obtain two low-frequency bandwidths using CAT. Coefficients within a low-frequency bandwidth are important information in an image. Hence, the difference between two low-frequency bandwidths is used as an important feature in the medical image. From these important features, watermarks and cover images can be used to generate an ownership share image (OSI) used for verifying the medical image. Besides appearing like cover images, the OSI will also be able to register with a third party. When a suspected medical image requires verification, the important features from the suspected medical image are first extracted. The master share image (MSI) can be generated from the important features from the suspected medical image. Lastly, the OSI and MSI can be combined to extract the watermark to verify the suspected medical image. The advantage of our proposed method is that the medical image does not require alteration to protect the copyright of the medical image. This means that while the image is protected, medical disputes will be unlikely and the appearance of the registered OSI will carry significant data to make management more convenient. Lastly, the proposed method has the features of having better security, invisibility, and robustness. Moreover, experimental results have demonstrated that our method results in good performance.

Visual perception based robust watermarking with integral imaging

This paper presents a robust watermarking approach for hiding gray watermark into digital images. Conventional transform-based watermarking schemes provide only one transform plane for watermark embedding, which makes easy to remove embedded watermark information. Cellular automata transform (CAT) based watermarking scheme can address this problem with CA properties. In this paper, the watermark is first recorded in the form of an elemental image array (EIA) with the computational integral imaging (CII) system, and then the recorded EIA is embedded into the CAT coefficient. The watermark embedding coefficient will be determined by an alpha map which generated by saliency map. This proposed method can provide a more robust watermarking system because EIA is composed of many elemental images and each image has its own property of the watermark. Even though most data of elemental images are lost, the watermark can be reconstructed successfully by using the remaining elemental images. Furthermore, the alpha map which is generated by saliency map can make watermark more invisible for the human visual system. Some experimental results show competence of our system.

Robust copyright protection using multiple ownership watermarks.

Generally, conventional transform (DWT and DFT, etc.) -based watermarking techniques provide only one spectrum plane for embedding the watermark, thus the embedding watermark information can be easily removed. To solve this problem, we propose an efficient cellular automata (CA) based watermarking method that CA transform (CAT) with various gateway values can provide many transform planes for watermark embedding according to various CA rules. In this paper, multiple ownership watermarks are first recorded in the form of an elemental image array (EIA), simultaneously, and then the recorded EIA as the watermark data is embedded into the CAT coefficient. An additional advantage of this proposed method is that EIA is composed of many elemental images and each elemental image has its own property of watermarks. Even though most data of elemental images are lost, the watermarks can be reconstructed from the remaining elemental images successfully. Experimental results show that the proposed technique provides good image quality and is robust in varying degree to some image processing attacks.

Gradual Encryption of Medical Image using Non-linear Cycle and 2D Cellular Automata Transform

In this paper, we propose on image encryption method which uses NC(Non-linear Cycle) and 2D CAT(Two-Dimensional Cellular Automata Transform) in sequence to encrypt medical images. In terms of the methodology, we use NC to generate a pseudo noise sequence equal to the size of the original image. We then conduct an XOR operation of the generated sequence with the original image to conduct level 1 NC encryption. Then we set the proper Gateway Values to generate the 2D CAT basis functions. We multiply the generated basis functions by the altered NC encryption image to conduct the 2nd level 2D CAT encryption. Finally, we verify that the proposed method is efficient and extremely safe by conducting an analysis of the key spatial and sensitivity analysis of pixels.

Improved integral imaging based image copyright protection algorithm using 3-D computational integral imaging pickup and super-resolution reconstruction technique

Cellular automata transform (CAT) based watermarking method can provide multi-transform planes for embedding watermark. In this paper, to overcome conventional transform-based watermarking methods have only one transform plane for watermark embedding, we propose a CAT-based watermarking system, in which the three-dimensional (3-D) watermark data is decomposed by the computational integral imaging (CII) technique and be embedded into the CAT domain. However, in the 3-D watermark reconstruction process, the computational integral imaging reconstruction (CIIR) technique in CII system that can degrade the quality of the extracted watermark due to the pixel overlapping. We introduce the super-resolution reconstruction technique that can effectively improve this problem. Some experiments are carried out to verify the performance of the CAT-based watermarking scheme. From the experimental results, the proposed watermarking system can provide good imperceptibility and high robustness.

A 3D image encryption technique using computer-generated integral imaging and cellular automata transform

A novel three-dimensional (3D) image encryption approach by using the computer-generated integral imaging and cellular automata transform (CAT) is proposed, in which, the two-dimensional (2D) elemental image array (EIA) digitally recorded by light rays coming from the 3D image is mapped inversely through the virtual pinhole array according to the ray-tracing theory. Next, the encrypted image is generated by using the 2D CAT scrambling transform for the 2D EIA. The reconstructed process is carried out by using the modified computational integral-imaging reconstruction (CIIR) technique; the depth-dependent plane images are reconstructed on the output plane. The reconstructed 3D image quality of the proposed scheme can be greatly improved, because the proposed encryption scheme carries out in a computer which can avoid the light diffraction caused by optical device CIIR, and solves blur problem caused by CIIR by using the pixel-averaging algorithm. Furthermore, the CAT-based encryption algorithm is an error-free encryption method; CAT as an orthogonal transformation offers considerable simplicity in the calculation of the transform coefficient, that is, it can improve the quality of the reconstructed image by reducing energy loss compared with the traditional complicated transform process. To show the effectiveness of the proposed scheme, we perform computational experiments. Experimental results show that the proposed scheme outperforms conventional encryption methods.

Computational integral imaging-based 3D digital watermarking scheme using cellular automata transform and maximum length cellular automata

A novel 3D watermarking algorithm by combining use of computational integral imaging (CII) and cellular automata transform (CAT) is proposed in this paper. In this proposed scheme, first, the original image signal is decomposed into three resolution levels by using the level-3 2D CAT, and meanwhile, the middle-frequency domains are obtained. Then, an elemental images (EIs) array is generated by recording the information of rays of light coming from an object through a pinhole array in the CII system. The EIs array is encrypted by linear maximum-length cellular automata as the encrypted watermark embedded into the CAT middle-frequency domains. Finally, the watermarked image is obtained by using the level-3 2D inverse CAT. To verify the usefulness of the proposed algorithm, we carry out the computational experiments and present the experimental results for various attacks. Experimental results show that this proposed watermarking system provides excellent results in unobtrusiveness and robustness.

Cellular Automata Transform based Invisible Digital Watermarking in Middle Domain for Gray Images

Cellular automata are discrete dynamical systems, which provide the basis for the synthesis of complex emergent behavior. This paper proposes a new algorithm of digital watermarking based on cellular automata transform (CAT). The idea of two-dimensional CAT is introduced into the algorithm. After the original image is disassembled with 2D CAT, the watermark information is embedded into the Middle-frequency of the carrier picture. Cellular automata have a huge number of combinations, such as gateway values, rule numbers, initial configuration, boundary condition, etc. Using CAT, the robustness of the watermark will be tremendous strengthened as well as its imperceptibility. Experimental results show that this algorithm can resist some usual attacks such as compression, sharpening and so on. The proposed method is robust to different attacks and is more security.

NBCA 에 기초한 여원 MLCA와 2D CAT를 이용한 새로운 영상 암호화

본 논문에서는 효율적인 영상 암호화를 위해 NBCA(Null Boundary CA)에 기초한 여원 MLCA(Maximum Length Cellular Automata)와 2D CAT(Two-Dimensional Cellular Automata Transform)를 이용한 암호화 방법을 제안한다. 암호화 방법은 먼저, Wolfram Rule 행렬에 의해 전이행렬 T를 생성한다. 그 후, 암호화하려는 원영상에 생성된 전이 행렬 T를 곱하여 원 영상의 픽셀 값을 변환한다. 또한 변환된 원 영상을 여원 벡터 F와 XOR 연산하여 여원 MLCA가 적용된 영상으로 변환한다. 다음, 게이트웨이 값을 설정하여 2D CAT 기저함수를 생성한다. 그리고, 여원 MLCA가 적용된 영상에 생성된 기저함수를 곱하여 2D CAT 암호화를 한다. 마지막으로 안정성 분석을 통하여 제안한 방법이 높은 암호화 수준의 성질을 가졌음을 검증한다. 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.

DWT와 셀룰라 오토마타 변환을 이용한 블라인드 워터마킹 비교

본 논문에서는 새로운 변환 기법인 셀룰라 오토마타 변환을 이용한 워터마킹 방법과 기존의 DWT를 이용한 방법을 비교한다. 이 두 방법 모두 서로 상반되는 임의의 패턴 정보를 사용하여 워터마크 정보를 영상에 삽입한다. 셀룰라 오토마타 변환은 DWT와 달리 더 많은 정보 즉, 룰 번호, 초기 값, 격자 크기 등 다양한 초기값을 이용하여 기저함수를 생성하여 변환한다. DWT와 셀룰라 오토마타 변환을 이용하여 변환된 영상의 계수를 분석 및 비교한 후 워터마킹 성능을 비교한다. 모의실험에서는 워터마크 정보가 삽입된 영상에 대한 PSNR 및 정규화 상관계수를 이용하여 원영상과의 가시적인 동일성과 다양한 외부 공격에 대한 강인성을 비교한다. 셀룰라 오토마타 변환을 이용한 워터마킹 방법이 DWT를 이용한 방법보다 JPEG 압축, 미디언 필터, 크기 변환, 잘라내기 및 히스토그램 평활화 등 대부분의 공격에 대하여 강인함을 보여준다. In this paper, we propose a novel blind digital watermarking method based on a cellular automata transform (CAT). CAT is based on dynamic systems known as cellular automata(CA) and uses transform bases which are differently defined by a rule number, the number of neighbors, the number of cells, and an initial state, etc. The proposed CAT based method is compared with a blind watermarking method based on DWT which is commonly used for a domain transform in signal processing. We analyse properties on changes of DWT coefficients and CAT coefficients under various attacks and determine optimal parameters for a watermarking method robust to attacks. The simulations show that the watermarked images with high PSNR and MSSIM look visually identical to originals and are robust against most of typical image processing attacks. Moreover, the proposed CAT based watermarking method is superior to the DWT based one in robustness to most of typical image processing attacks including JPEG compression, median and average filtering, scaling, cropping, and histogram equalization.