Application of visual cryptography for learning in optics and photonics

In the age data digitalization, important applications of optics and photonics based sensors and technology lie in the field of biometrics and image processing. Protecting user data in a safe and secure way is an essential task in this area. However, traditional cryptographic protocols rely heavily on computer aided computation. Secure protocols which rely only on human interactions are usually simpler to understand. In many scenarios development of such protocols are also important for ease of implementation and deployment. Visual cryptography (VC) is an encryption technique on images (or text) in which decryption is done by human visual system. In this technique, an image is encrypted into number of pieces (known as shares). When the printed shares are physically superimposed together, the image can be decrypted with human vision. Modern digital watermarking technologies can be combined with VC for image copyright protection where the shares can be watermarks (small identification) embedded in the image. Similarly, VC can be used for improving security of biometric authentication. This paper presents about design and implementation of a practical laboratory experiment based on the concept of VC for a course in media engineering. Specifically, our contribution deals with integration of VC in different schemes for applications like digital watermarking and biometric authentication in the field of optics and photonics. We describe theoretical concepts and propose our infrastructure for the experiment. Finally, we will evaluate the learning outcome of the experiment, performed by the students

Multibiometric security in wireless communication systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition. First is the enrolment phase by which the database of watermarked fingerprints with memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel. Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present one’s fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user. The following three steps then involve speaker recognition including the user responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user. In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and sliding neighborhood) have been followed with further two steps for embedding, and extracting the watermark into the enhanced fingerprint image utilising Discrete Wavelet Transform (DWT). In the speaker recognition stage, the limitations of this technique in wireless communication have been addressed by sending voice feature (cepstral coefficients) instead of raw sample. This scheme is to reap the advantages of reducing the transmission time and dependency of the data on communication channel, together with no loss of packet. Finally, the obtained results have verified the claims

A Fingerprint-Based Digital Images Watermarking for Identity Authentication

In this paper the combination of fingerprint verification methods with watermarkingtechnology to provide copyright protection and authentication of digital images is proposed. The goalof this study is to investigate how watermarking processing affects the quality of biometric watermarks.Performed experiments showed that extracted fingerprint images have roughly equal verification performance even if some watermarked images undergo additional degradation. Proposed methodologywill be improved using more sophisticated fingerprint verification methods and subsequently incorporated into multimodal watermarking schemes

Fingerprint Authentication by Wavelet-based Digital Watermarking

In this manuscript, a wavelet-based blind watermarking scheme has been proposed as a means to provide protection against false matching of a possibly tampered fingerprint by embedding a binary name label of the fingerprint owner in the fingerprint itself. Embedding watermarks in the detail regions allow us to increase the robustness of our watermark, at little to no additional impact on image quality. It has been experimentally shown that when a binary watermark is embedded into detail coefficients of an indexed fingerprint image in a spread spectrum fashion, the perceptual invisibility and robustness have anticlinal response to change in amplification factor “K” and smaller watermarks have better transparency than the larger ones. The DWT-based technique has been found to give better robustness against noises, geometrical distortions, filtering and JPEG compression attack than other frequency domain watermarking techniques.DOI:http://dx.doi.org/10.11591/ijece.v2i4.50

Region-Based Watermarking of Biometric Images: Case Study in Fingerprint Images

In this paper, a novel scheme to watermark biometric images is proposed. It exploits the fact that biometric images, normally, have one region of interest, which represents the relevant part of information processable by most of the biometric-based identification/authentication systems. This proposed scheme consists of embedding the watermark into the region of interest only; thus, preserving the hidden data from the segmentation process that removes the useless background and keeps the region of interest unaltered; a process which can be used by an attacker as a cropping attack. Also, it provides more robustness and better imperceptibility of the embedded watermark. The proposed scheme is introduced into the optimum watermark detection in order to improve its performance. It is applied to fingerprint images, one of the most widely used and studied biometric data. The watermarking is assessed in two well-known transform domains: the discrete wavelet transform (DWT) and the discrete Fourier transform (DFT). The results obtained are very attractive and clearly show significant improvements when compared to the standard technique, which operates on the whole image. The results also reveal that the segmentation (cropping) attack does not affect the performance of the proposed technique, which also shows more robustness against other common attacks

An Efficient Fingerprint Enhancement Technique Using Wave Atom Transform and MCS Algorithm

AbstractFingerprints are widely and successfully used for personal identification. This is mainly due to their individuality, stability through life, uniqueness among people, public acceptance and their minimum risk of intrusion. Fingerprint technology is a biometric technique utilized to identify persons based on their physical traits. The physical patterns of this technique consist of ridges and valleys that exist on the surface of fingertips. Fingerprint images are direction-oriented patterns formed by ridges and valleys. The eminence of the fingerprint image is determined by the sturdiness of a fingerprint authentication system. In order to improve the limitations of existing fingerprint image enhancement methods an efficient technique is proposed to deal with low quality fingerprint images. The proposed methodology can be divided into three modules. In the first module, the fingerprint image is subjected to denoising process where Wave atom transform is utilized. After the completion of this process the image enhancement is performed with the help of optimization algorithm. In our enhancement approach, a Modified Cuckoo Search (MCS) algorithm is used as an optimizer. This helps to look for the best gray level distribution that maximizes the objective function

An overview of touchless 2D fingerprint recognition

Touchless fingerprint recognition represents a rapidly growing field of research which has been studied for more than a decade. Through a touchless acquisition process, many issues of touch-based systems are circumvented, e.g., the presence of latent fingerprints or distortions caused by pressing fingers on a sensor surface. However, touchless fingerprint recognition systems reveal new challenges. In particular, a reliable detection and focusing of a presented finger as well as an appropriate preprocessing of the acquired finger image represent the most crucial tasks. Also, further issues, e.g., interoperability between touchless and touch-based fingerprints or presentation attack detection, are currently investigated by different research groups. Many works have been proposed so far to put touchless fingerprint recognition into practice. Published approaches range from self identification scenarios with commodity devices, e.g., smartphones, to high performance on-the-move deployments paving the way for new fingerprint recognition application scenarios.This work summarizes the state-of-the-art in the field of touchless 2D fingerprint recognition at each stage of the recognition process. Additionally, technical considerations and trade-offs of the presented methods are discussed along with open issues and challenges. An overview of available research resources completes the work

An Efficient Fingerprint Identification using Neural Network and BAT Algorithm

The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor