A New Fractional Random Wavelet Transform for Fingerprint Security

A new 1D chaotic system for image encryption

Abstract: This paper introduces a simple and effective chaotic system using a combination of two existing one-dimension (1D) chaotic maps (seed maps). Simulations and performance evaluations show that the proposed system is able to produce many 1D chaotic maps with larger chaotic ranges and better chaotic behaviors compared with their seed maps. To investigate its applications in multimedia security, a novel image encryption algorithm is proposed. Using a same set of security keys, this algorithm is able to generate a completely different encrypted image each time when it is applied to the same original image. Experiments and security analysis demonstrate the algorithm's excellent performance in image encryption and various attacks.

A new color image encryption using combination of the 1D chaotic map

Abstract: One method of making a simple and effective chaotic system by using different outputs sequences of two same existing 1D chaotic maps was introduced.A novel encryption system of linear-nonlinear-linear structure based on total shuffling was proposedThe experimental results show the proposed encryption algorithm has excellent performance in noise and attacks This paper introduces a method of making a simple and effective chaotic system by using a difference of the output sequences of two same existing one-dimension (1D) chaotic maps. Simulations and performance evaluations show that the proposed system is able to produce a one-dimension (1D) chaotic system with better chaotic performances and larger chaotic ranges compared with the previous chaotic maps. To investigate its applications in image encryption, a novel encryption system of linear-nonlinear-linear structure based on total shuffling is proposed. The experiment demonstrated the accuracy of the encryption algorithm. Experiments and security analysis prove that the algorithm has an excellent performance in image encryption and various attacks.

Multimodal fusion framework: a multiresolution approach for emotion classification and recognition from physiological signals.

Abstract: The purpose of this paper is twofold: (i) to investigate the emotion representation models and find out the possibility of a model with minimum number of continuous dimensions and (ii) to recognize and predict emotion from the measured physiological signals using multiresolution approach. The multimodal physiological signals are: Electroencephalogram (EEG) (32 channels) and peripheral (8 channels: Galvanic skin response (GSR), blood volume pressure, respiration pattern, skin temperature, electromyogram (EMG) and electrooculogram (EOG)) as given in the DEAP database. We have discussed the theories of emotion modeling based on i) basic emotions, ii) cognitive appraisal and physiological response approach and iii) the dimensional approach and proposed a three continuous dimensional representation model for emotions. The clustering experiment on the given valence, arousal and dominance values of various emotions has been done to validate the proposed model. A novel approach for multimodal fusion of information from a large number of channels to classify and predict emotions has also been proposed. Discrete Wavelet Transform, a classical transform for multiresolution analysis of signal has been used in this study. The experiments are performed to classify different emotions from four classifiers. The average accuracies are 81.45%, 74.37%, 57.74% and 75.94% for SVM, MLP, KNN and MMC classifiers respectively. The best accuracy is for 'Depressing' with 85.46% using SVM. The 32 EEG channels are considered as independent modes and features from each channel are considered with equal importance. May be some of the channel data are correlated but they may contain supplementary information. In comparison with the results given by others, the high accuracy of 85% with 13 emotions and 32 subjects from our proposed method clearly proves the potential of our multimodal fusion approach.

A New Human Identification Method: Sclera Recognition

Abstract: The blood vessel structure of the sclera is unique to each person, and it can be remotely obtained nonintrusively in the visible wavelengths. Therefore, it is well suited for human identification (ID). In this paper, we propose a new concept for human ID: sclera recognition. This is a challenging research problem because images of sclera vessel patterns are often defocused and/or saturated and, most importantly, the vessel structure in the sclera is multilayered and has complex nonlinear deformations. This paper has several contributions. First, we proposed the new approach for human ID: sclera recognition. Second, we developed a new method for sclera segmentation which works for both color and grayscale images. Third, we designed a Gabor wavelet-based sclera pattern enhancement method to emphasize and binarize the sclera vessel patterns. Finally, we proposed a line-descriptor-based feature extraction, registration, and matching method that is illumination, scale, orientation, and deformation invariant and can mitigate the multilayered deformation effects and tolerate segmentation error. The experimental results show that sclera recognition is a promising new biometrics for positive human ID.

An overview of encryption algorithms in color images

Abstract: Nowadays, security in data transfer is of special importance. Images are of the most attractive kinds of data in the encryption domain. Color images are more attractive than the gray-level images due to provision of more information. In the present study, various existing color (RGB mode) image encryption schemes have been examined comprehensively based on the application domains in addition to summarizing over 50 studies in this field, most of which being published in the last year. In addition, in this study, color image encryption has been categorized into ten schemes, then the proposed schemes have been compared and their advantages and limitations have been highlighted. Moreover, a complete list of common security analysis techniques for (gray or color) image encryption has been discussed which are capable of evaluating the method potential resistance to different possible attacks. The present study has been carried out to provide detailed knowledge regarding the existing image encryption schemes in the area of the RGB images. Finally, in the current study, various open issues and research directions have been considered in order to explore the promising areas for future developments.

A theory for multiresolution signal decomposition: the wavelet representation

Abstract: Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions. In L/sup 2/(R), a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi (x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. Wavelet representation lies between the spatial and Fourier domains. For images, the wavelet representation differentiates several spatial orientations. The application of this representation to data compression in image coding, texture discrimination and fractal analysis is discussed. >

Handbook of Applied Cryptography

Abstract: From the Publisher: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.

The Fourier Transform and Its Applications

Abstract: 1 Introduction 2 Groundwork 3 Convolution 4 Notation for Some Useful Functions 5 The Impulse Symbol 6 The Basic Theorems 7 Obtaining Transforms 8 The Two Domains 9 Waveforms, Spectra, Filters and Linearity 10 Sampling and Series 11 The Discrete Fourier Transform and the FFT 12 The Discrete Hartley Transform 13 Relatives of the Fourier Transform 14 The Laplace Transform 15 Antennas and Optics 16 Applications in Statistics 17 Random Waveforms and Noise 18 Heat Conduction and Diffusion 19 Dynamic Power Spectra 20 Tables of sinc x, sinc2x, and exp(-71x2) 21 Solutions to Selected Problems 22 Pictorial Dictionary of Fourier Transforms 23 The Life of Joseph Fourier

Cryptography and Network Security: Principles and Practice

Abstract: William Stallings' Cryptography and Network Security: Principles and Practice, 5e is a practical survey of cryptography and network security with unmatched support for instructors and students. In this age of universal electronic connectivity, viruses and hackers, electronic eavesdropping, and electronic fraud, security is paramount. This text provides a practical survey of both the principles and practice of cryptography and network security. First, the basic issues to be addressed by a network security capability are explored through a tutorial and survey of cryptography and network security technology. Then, the practice of network security is explored via practical applications that have been implemented and are in use today. An unparalleled support package for instructors and students ensures a successful teaching and learning experience. The new edition has been updated to include coverage of the latest topics including expanded coverage of block cipher modes of operation, including authenticated encryption; revised and expanded coverage of AES; expanded coverage of pseudorandom number generation; new coverage of federated identity, HTTPS, Secure Shell (SSH) and wireless network security; completely rewritten and updated coverage of IPsec; and a new chapter on legal and ethical issues.

FSIM: A Feature Similarity Index for Image Quality Assessment

Abstract: Image quality assessment (IQA) aims to use computational models to measure the image quality consistently with subjective evaluations. The well-known structural similarity index brings IQA from pixel- to structure-based stage. In this paper, a novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimensionless measure of the significance of a local structure, is used as the primary feature in FSIM. Considering that PC is contrast invariant while the contrast information does affect HVS' perception of image quality, the image gradient magnitude (GM) is employed as the secondary feature in FSIM. PC and GM play complementary roles in characterizing the image local quality. After obtaining the local quality map, we use PC again as a weighting function to derive a single quality score. Extensive experiments performed on six benchmark IQA databases demonstrate that FSIM can achieve much higher consistency with the subjective evaluations than state-of-the-art IQA metrics.