A new scheme of image watermarking based onfuzzy clustering theory

Today, the Internet is a worldwide broadcasting capability, a mechanism for information dissemination and a medium for collaboration and interaction between individuals and their computers without regard for geographic location. With the rapid evolution of digital networks, digital libraries and World Wide Web (WWW) services, the convenient broadcasting or exposition of digital products on the global network leads easily to illegal copying, modifying and retransmission. The Internet has spawned many copyright issues involving multimedia content distribution. Let’s say an owner would like to sell or distribute a work to legal/registered users only. If the work were subsequently copied/redistributed illegally, how could the owner find who was responsible? Cryptographic techniques provide an effective solution for securing the delivery process and controlling the use of the contents that an user has obtained. However, with flawless transmission through the network, the contents after decryption are exactly the same as the original data. The contents can be copied perfectly infinite times. A user can also manipulate the contents. Digital watermarking (Arnold, Schmucker, & Wolthusen, 2003; Katzenbeisser & Petitcolas, 2000) offers a way to counter copyright piracy on global networks that are not solvable by cryptography. It provides proof and tracking capabilities to illegal copying and distribution of multimedia information. Most existing digital watermarking schemes are based on some assumptions for watermark detection and extraction. Some schemes require the previous knowledge of watermark locations, strengths or some thresholds. In some algorithms, the watermark is estimated with the help of the original watermark information. To ensure the robustness and invisibility of the watermark, the optimum embedding locations are usually different for different images. For a large image database, it could be a disadvantage to require watermark location and strength information for watermark detection and extraction. A large amount of information then needs to be stored. On the Internet, an owner would like to distribute multimedia data by signing different watermarks to different users in order to prevent illegal redistribution of the data by a legal user. In this scenario, watermark detection and extraction algorithms requiring information of either watermark embedding locations and strengths or the original watermark should fail, since one does not know exactly which watermark is embedded in a particular copy of the watermarked image. To this end, we present a new blind watermarking scheme (Yu, Sattar, & Ma, 2002; Yu & Sattar, 2003, 2005) based on Independent Component Analysis (ICA) (Hyvarinen, 1999; Hyvärinen & Oja, 1999; Lee, 1998) for color images, which can overcome existing problems of watermark detection and extraction as described above. The new ICA-based scheme is found to be efficient in the application of data tracking/tracing for multimedia distribution through the Internet against other digital watermarking schemes. By adopting this ICA-based watermarking scheme, an efficient multimedia distribution framework/protocol for copyright protection can be accomplished. This article is organized as follows: The watermark embedding and extraction algorithms for color image watermarking using the new ICA-based scheme are presented next, followed by a discussion and comments on the results, security issues, summary and future works.

Today, the Internet is a worldwide broadcasting capability, a mechanism for information dissemination and a medium for collaboration and interaction between individuals and their computers without regard for geographic location. With the rapid evolution of digital networks, digital libraries and World Wide Web (WWW) services, the convenient broadcasting or exposition of digital products on the global network leads easily to illegal copying, modifying and retransmission. The Internet has spawned many copyright issues involving multimedia content distribution. Let’s say an owner would like to sell or distribute a work to legal/registered users only. If the work were subsequently copied/redistributed illegally, how could the owner find who was responsible? Cryptographic techniques provide an effective solution for securing the delivery process and controlling the use of the contents that an user has obtained. However, with flawless transmission through the network, the contents after decryption are exactly the same as the original data. The contents can be copied perfectly infinite times. A user can also manipulate the contents. Digital watermarking (Arnold, Schmucker, & Wolthusen, 2003; Katzenbeisser & Petitcolas, 2000) offers a way to counter copyright piracy on global networks that are not solvable by cryptography. It provides proof and tracking capabilities to illegal copying and distribution of multimedia information. Most existing digital watermarking schemes are based on some assumptions for watermark detection and extraction. Some schemes require the previous knowledge of watermark locations, strengths or some thresholds. In some algorithms, the watermark is estimated with the help of the original watermark information. To ensure the robustness and invisibility of the watermark, the optimum embedding locations are usually different for different images. For a large image database, it could be a disadvantage to require watermark location and strength information for watermark detection and extraction. A large amount of information then needs to be stored. On the Internet, an owner would like to distribute multimedia data by signing different watermarks to different users in order to prevent illegal redistribution of the data by a legal user. In this scenario, watermark detection and extraction algorithms requiring information of either watermark embedding locations and strengths or the original watermark should fail, since one does not know exactly which watermark is embedded in a particular copy of the watermarked image. To this end, we present a new blind watermarking scheme (Yu, Sattar, & Ma, 2002; Yu & Sattar, 2003, 2005) based on Independent Component Analysis (ICA) (Hyvarinen, 1999; Hyvärinen & Oja, 1999; Lee, 1998) for color images, which can overcome existing problems of watermark detection and extraction as described above. The new ICA-based scheme is found to be efficient in the application of data tracking/tracing for multimedia distribution through the Internet against other digital watermarking schemes. By adopting this ICA-based watermarking scheme, an efficient multimedia distribution framework/protocol for copyright protection can be accomplished. This article is organized as follows: The watermark embedding and extraction algorithms for color image watermarking using the new ICA-based scheme are presented next, followed by a discussion and comments on the results, security issues, summary and future works.

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon the accuracy and robustness of the thermal error model and its input measurements. This paper first reviews different methods of designing thermal error models, before concentrating on employing an adaptive neuro fuzzy inference system (ANFIS) to design two thermal prediction models: ANFIS by dividing the data space into rectangular sub-spaces (ANFIS-Grid model) and ANFIS by using the fuzzy c-means clustering method (ANFIS-FCM model). Grey system theory is used to obtain the influence ranking of all possible temperature sensors on the thermal response of the machine structure. All the influence weightings of the thermal sensors are clustered into groups using the fuzzy c-means (FCM) clustering method, the groups then being further reduced by correlation analysis.A study of a small CNC milling machine is used to provide training data for the proposed models and then to provide independent testing data sets. The results of the study show that the ANFIS-FCM model is superior in terms of the accuracy of its predictive ability with the benefit of fewer rules. The residual value of the proposed model is smaller than ±4μm. This combined methodology can provide improved accuracy and robustness of a thermal error compensation system.

The rolling bearings are considered as the heart of rotating machinery and early fault diagnosis is one of the biggest challenges during operation. Due to complicated mechanical assemblies, detection of the advancing fault and faults at the incipient stage is very difficult and tedious. This work presents a fuzzy rule based classification of bearing faults using Fuzzy C-means clustering method using vibration measurements. Experiments were conducted to collect the vibration signals of a normal bearing and bearings with faults in the inner race, outer race and ball fault. Discrete Wavelet Transform (DWT) technique is used to decompose the vibration signals into different frequency bands. In order to detect the early faults in the bearings, various statistical features were extracted from this decomposed signal of each frequency band. Based on the extracted features, Fuzzy C-means clustering method (FCM) is developed to classify the faults using suitable membership functions and fuzzy rule base is developed for each class of the bearing fault using labeled data. The experimental results show that the proposed method is able to classify the condition of the bearing using the extracted features. The proposed FCM based clustering and classification model provides easier interpretation and implementation for monitoring the condition of the rolling bearings at an early stage and it will be helpful to take the preventive action before a large-scale failure.

In modern times, the rapid growth of the Internet has made copyright protection of digital contents a critical issue. A Digital Rights Management (DRM) system is aimed at protecting the high-value digital assets and controlling the distribution and utilization of those digital assets. Watermarking technologies are being regarded as a vital mean to proffer copyright protection of digital images. Digital watermarking hides, in digital images, the information necessary for ownership identity to offer copyright protection. This paper proposes an innovative invisible and blind watermarking scheme for copyright protection of digital images with the purpose of defending against digital piracy. In the proposed watermarking scheme, a binary watermark image is invisibly embedded into the host image for achieving copyright protection. In watermark embedding, every pixel of the watermark image is embedded into the individual blocks of the host image sized 2×2. In the proposed watermarking scheme, the process of watermark extraction necessitates only the watermarked image and it doesn't require the original image or any of its characteristics, and hence, the proposed watermarking scheme is blind. The efficiency of the proposed watermarking scheme has been demonstrated via the experimental results.

In recent years, with the rapid development of internet, digital data has been widely used in various science and engineering applications. But, this development has also led to several threats and attacks from the intruders. Most of the organizations are very much concerned about the Illegal copyright activities which have become a series issue. A number of copyright protection schemes have been developed in the literature. Watermarking is one of the best known methods for copyright protection. Earlier Bit Error Rate (BER) is been observed to provide good results for choosing the optimal feature region from the watermarked image. However it fails to produce more accurate image quality measures. This research work mainly focuses on a novel technique implemented based on the simulated attacking approach and the GA-based Multi Dimensional Knapsack Problem (MDKP) solving technique to select the most sufficient feature regions for robust digital image watermarking without affecting the image quality. A major limitation in existing methods is the security problems which lead to decrease in the integrity of digital watermarking scheme. With that problem, the definite optimization problems (variant problems) cannot be resolved using genetic algorithms. To focus on the above mentioned problems, the proposed work uses two approaches. Chaotic Iterative Process encryption scheme is used to solve the security problems for watermarking image. Next, the optimal feature points can be chosen from the watermarked image by Modified version of Peak Signal Noise Ratio (MPSNR). MPSNR is based on the enhanced quality measurement of which point opposes the predefined and undefined attacks. With those two approaches the PSO algorithm is employed as a search strategy for identifying an optimal feature subset. The experimental results illustrates that comparing with various well-known feature-based techniques, the proposed method shows better performance in robust and more secure digital watermarking.

Fuzzy C-means (FCM) clustering method has been widely used in image segmentation that plays an important role in a variety of applications in image processing and computer vision systems, but the performance of FCM heavily relies on the initial cluster centers which are difficult to determine. To solve the problem, the paper proposes a new hybrid method for image segmentation, which first randomly generates a population of initial clustering solutions and then uses an evolutionary algorithm to search for better clustering solutions; at each iteration, the FCM method is applied on each initial clustering solution to produce its segmentation result. Among a set of popular evolutionary algorithms, we find that the biogeography-based optimization (BBO) metaheuristic exhibits good performance on the considered problem. Besides the basic BBO, we have also proposed a set of improved BBO versions in their combination with FCM for image segmentation. Computational experiments on a set of test images show that the proposed method has significant advantage over the basic FCM algorithm and those hybrid algorithms combining FCM with other evolutionary algorithms such as artificial bee colony and particle swarm optimization.

This article is focused in developing an improved cluster ensemble method based cluster forests. Cluster forests (CF) is considered as a version of clustering inspired from Random Forests (RF) in the context of clustering for massive data. It aggregates intermediate Fuzzy C-Means (FCM) clustering results via spectral clustering since pseudo-clustering results are presented in the spectral space in order to classify these data sets in the multidimensional data space. One of the main advantages is the use of FCM, which allows building fuzzy membership to all partitions of the datasets due to the fuzzy logic whereas the classical algorithms as K-means permitted to build just hard partitions. In the first place, we ameliorate the CF clustering algorithm with the integration of fuzzy FCM and we compare it with other existing clustering methods. In the second place, we compare K-means and FCM clustering methods with the agglomerative hierarchical clustering (HAC) and other theory presented methods using data benchmarks from UCI repository.

Although digitalization and the Internet are very convenient and useful for personal users and industry, they suffer from shortcomings of security. For instance, private content is difficult to protect and fake versions of multimedia data can be produced. Digital watermarking offers some effective solutions. This work presents a video watermarking scheme that uses motion vectors to define the place where the watermarks are embedded, and the number of watermark bits vary dynamically among frames. Fuzzy C-means (FCM) clustering method is utilized to select the motion vectors and the positions of the watermarks. The advantages of this work are twofold. A novel watermarking strategy is presented that does not require manual selection of watermark bits location. The number of embedded motion vector clusters differs depending on the motion characteristics in each frame. This significant property possesses higher security. As can be concluded from the experimental results, the watermarked video retains satisfactory quality with very small degradation.

In fuzzy C-means (FCM) clustering, each data point belongs to a cluster to a degree specified by a membership grade. FCM partitions a collection of vectors in c fuzzy groups and finds a cluster center in each group such that the dissimilarity measure is minimized. This paper presents a training algorithm for the radial basis function (RBF) network using symmetry-based Fuzzy C-means (SFCM) clustering method which is the modified version of FCM clustering method based on point symmetry distance measure. The training algorithm which uses SFCM clustering method to train the network has a number of advantages such as faster training time, more accurate predictions and reduced network architecture compared to the standard RBF networks. The proposed training algorithm has been implemented in the RBF networks created by the newrb function of MATLAB which uses gradient based iterative method as learning strategy, therefore the new network will undergo a hybrid learning process. The networks called Symmetry-based Fuzzy C-means Clustering–Radial Basis Function Network (SFCM/RBF) has been tested against the standard RBF network and the networks called standard Fuzzy C-means Clustering (FCM)-RBF network (FCM/RBF) in forecasting. The experimental models has been tested on three real world application problems, particularly in Air pollutant problem, Biochemical Oxygen Demand (BOD) problem, and Phytoplankton problem. Keywords: Fuzzy c-means clustering; SFCM; Radial basis function network; point symmetry distance; forecasting.

The security of a watermarking scheme is mainly categorised as either robust or fragile. The former can withstand an authorised alteration/attack, primarily used in copyright protection. The latter follows a zero tolerance towards any modification, used primarily in content authentication processes. The existing literature in the field projects that two separate watermarks are required to make a watermarking scheme robust and fragile, thus making the overall process cumbersome and complex. A novel image watermarking scheme that uses only one watermark while achieving both goals of copyright protection and authentication of identities is presented. An unconventional concept of checkpointing is introduced, which equips the proposed scheme to be either robust or fragile, making it superior in its application versatility. First, watermark embedding within the host/original image is achieved by a combination of transform domain techniques along with a novel median-based embedding block selection procedure. Second, checkpointing is performed in the spatial domain. The watermarked image in the absence of an attack is correlated to the one that is being attacked, using the template energy comparison-based approach. In the case of the robust watermark, such checkpointing can establish whether the carried out attack is authorised or not, determining the successful recovery of the watermark or vice-versa. Moreover, in the case of the fragile watermark, a sole confirmation of the occurrence of an attack is sufficient to make the watermark recovery impossible. Finally, the experimental analysis of the proposed scheme illustrates its excellent performance and superiority over state-of-the-art methods within the field.

Region segmentation is one of the most common methods of medical image segmentation. However, it still has some disadvantages in practice: (1) Threshold choice will result in a poor performance in the image segmentation if there is little difference in the gray of an image. (2) Region-based segmentation algorithm is usually uncertain in defining the edge between the object and the background. This paper implements an improved algorithm to overcome these problems. In the algorithm, the FCM (fuzzy C-means) clustering method is used to improve the accuracy of image segmentation according to its stability. And Roberts operator is also added to compensate the deficiency in edge detection. This medical image segmentation method is a combination of region segmentation and edge segmentation, which is based on OTSU threshold segmentation, fuzzy C-means clustering and Roberts operator. Experiments show that the improved segmentation algorithm has a better performance than those traditional algorithms in the effect.

Quantization parameter based blind watermarking schemes are very popular. These schemes work in spatial domain as well as in various transform domains such as wavelet, discrete cosine, and real oriented wavelet. These schemes utilize one bit (binary) image as a watermark. However, in general, watermarks are any n bit image, where n ≥ 1. Therefore, these schemes are not suitable for the watermarks with n > 1. In this paper, we extend the existing work on blind watermarking schemes for n bits watermark images. The ‘division algorithm’ is used as a key component to develop the extended schemes. The proposed scheme is implemented in spatial domain. Experiments are done on one bit, two bits and eight bits watermark images. The results are investigated qualitatively by visualization, and measured quantitatively by peak-signal-to-noise-ratio (PSNR) and normalized correlation coefficient (NC). The results of the existing and proposed watermarking schemes are same for n = 1. The results of the proposed watermarking scheme are reliable for n > 1. A formula is proven for lower bound on PSNR, which is a key finding in the watermarking community. The formula is verified experimentally.

With the rapid growth of the multimedia technology, copyright protection has become a very important issue, especially for images. The advantages of easy photo distribution are discarded by their possible theft and unauthorized usage on different websites. Therefore, there is a need in securing information with technical methods, for example digital watermarks. This paper reviews digital watermark embedding methods for image copyright protection, advantages and disadvantages of digital watermark usage are produced. Different watermarking algorithms are analyzed. Based on analysis results most effective algorithm is chosen – differential energy watermarking. It is noticed that the method excels at providing image integrity. Digital watermark embedding system should prevent illegal access to the digital watermark and its container. Requirements for digital watermark are produced. Possible image attacks are reviewed. Modern modifications of embedding algorithms are studied. Robustness of the differential energy watermark is investigated. Robustness is a special value, which formulae is given further in the article. DEW method modification is proposed, it’s advantages over original algorithm are described. Digital watermark serves as an additional layer of defense which is in most cases unknown to the violator. Scope of studied image attacks includes compression, filtration, scaling. In conclusion, it’s possible to use DEW watermarking in copyright protection, violator can easily be detected if images with embedded information are exchanged.

This paper presents a confidential text documents leakage investigation system, focused on leak channels by documents printing and screen photographing. Internal intruders may print confidential document, take paper copy out of protected perimeter, make document image by scanner and perform anonymous leak. Also, intruders may take a photo of printed confidential document or displayed on workstation screen using personal mobile phone. Described leakage channels are weakly covered by traditional DLP systems that are usually used by enterprises for confidential information leak protection. Digital watermark (DWM) embedding is chosen as a document protection mechanism by implying changing of document image visual representation. In case of confidential document anonymous leak embedded DWM would enable the employee to determine what leak intentionally or by security protocol violation. System architecture consists of different type components. Employees’ workstation components provide DWM embedding into documents, which are sent for printing or displayed on screen. Information about watermark embedding is sent to a remote server that aggregates marking facts and provides it to security officer during investigation. Text document marking algorithms are developed, which embed DWM into printed and displayed on screen documents. Screen watermark is embedded into interline space interval, information is encoded by sequence of lightened and darkened spaces. DWM embedding into printed documents is implemented by three algorithms: horizontal and vertical shift based, font fragments brightness changing based. Algorithms testing methodology is developed in view of the production environment, that helped to evaluate the application area of algorithms. Besides, intruder model was formulated, system security was evaluated and determined possible attack vectors.