Cesar O. Torres

Digital Images Phase Encryption Using Fractional Fourier Transform

In the present paper the fractional Fourier transform was used to make phase encryption of color digital images. The image to encrypt is placed as the phase of a complex exponential, then is fractionally transformed three times and multiplied in intermediate steps by two statistically independent random phase masks thus to obtain the encrypted image, to decrypt the coding image the encryption procedure is applied in the inverse sense to the conjugated complex of the encrypted image, then is taken the negative of the phase of the resulting function from the decryption process and the original image is obtained this way that had been encrypted. The use of the fractional Fourier transform and the phase encryption of the image add much more complexity to the decryption of the image to who wants decrypt it without being authorized. In the cryptographic algorithm implemented five keys are used, made up of three fractional orders and two random phase masks, all these keys are necessary for proper decryption affording reliability to image transference via transmission networks

Image encryption using the fractional wavelet transform

In this paper a technique for the coding of digital images is developed using Fractional Wavelet Transform (FWT) and random phase masks (RPMs). The digital image to encrypt is transformed with the FWT, after the coefficients resulting from the FWT (Approximation, Details: Horizontal, vertical and diagonal) are multiplied each one by different RPMs (statistically independent) and these latest results is applied an Inverse Wavelet Transform (IWT), obtaining the encrypted digital image. The decryption technique is the same encryption technique in reverse sense. This technique provides immediate advantages security compared to conventional techniques, in this technique the mother wavelet family and fractional orders associated with the FWT are additional keys that make access difficult to information to an unauthorized person (besides the RPMs used), thereby the level of encryption security is extraordinarily increased. In this work the mathematical support for the use of the FWT in the computational algorithm for the encryption is also developed.

Fractional Hartley transform applied to optical image encryption

A new method for image encryption is introduced on the basis of two-dimensional (2-D) generalization of 1-D fractional Hartley transform that has been redefined recently in search of its inverse transform We encrypt the image by two fractional orders and random phase codes. It has an advantage over Hartley transform, for its fractional orders can also be used as addictional keys, and that, of course, strengthens image security. Only when all of these keys are correct, can the image be well decrypted. Computer simulations are also perfomed to confirm the possibilty of proposed method.

Sign Language Recognition System using Neural Network for Digital Hardware Implementation

This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

Double image encryption method using the Arnold transform in the fractional Hartley domain

A new method for double image encryption based on the fractional Hartley transform (FrHT) and the Arnold transform (AT) is proposed in this work. The encryption method encodes the first input image in amplitude and the second input image is encoded in phase, in order to define a complex image. This complex image is successively four times transformed using FrHT and AT, and the resulting complex image represents the encrypted image. The decryption method is the same method as the encryption method applied in the inverse sense. The AT is a process of image shearing and stitching in which pixels of the image are rearranged. This AT is used in the encryption method with the purpose of spreading the information content of the two input images onto the encrypted image and to increase the security of the encrypted image. The fractional orders of the FrHTs and the parameters of the ATs correspond to the keys of the encryption-decryption method. Only when all of those keys are correct in the decryption method, the two original images can be recovered. We present digital results that confirm our approach.

Image segmentation blood vessel of retinal using conventional filters, Gabor Transform and skeletonization

This paper implements a digital algorithm that allows the segmentation and skeletonization of digital images, this method is very important in the processing of retinographies images, where of analysis inside of the eye enables early detection of diseases such as Diabetic Retinopathy. The algorithm implemented using the Fourier transforms and Gabor Transform two-dimensional and conventional filters. The performance of algorithm under mathematical platform the Matlab implemented has been compared with conventional methods obtaining resulting filtered images with better contrast and higher resolution.

Radial Hilbert Transform in terms of the Fourier Transform applied to Image Encryption

In the present investigation, a mathematical algorithm under Matlab platform using Radial Hilbert Transform and Random Phase Mask for encrypting digital images is implemented. The algorithm is based on the use of the conventional Fourier transform and two random phase masks, which provide security and robustness to the system implemented. Random phase masks used during encryption and decryption are the keys to improve security and make the system immune to attacks by program generation phase masks.

Design and implementation in VHDL code of the two- dimensional fast Fourier transform for frequency filtering, convolution and correlation operations

The two-dimensional Fast Fourier Transform (FFT 2D) is an essential tool in the two-dimensional discrete signals analysis and processing, which allows developing a large number of applications. This article shows the description and synthesis in VHDL code of the FFT 2D with fixed point binary representation using the programming tool Simulink HDL Coder of Matlab; showing a quick and easy way to handle overflow, underflow and the creation registers, adders and multipliers of complex data in VHDL and as well as the generation of test bench for verification of the codes generated in the ModelSim tool. The main objective of development of the hardware architecture of the FFT 2D focuses on the subsequent completion of the following operations applied to images: frequency filtering, convolution and correlation. The description and synthesis of the hardware architecture uses the XC3S1200E family Spartan 3E FPGA from Xilinx Manufacturer.

Template characterization and correlation algorithm created from segmentation for the iris biometric authentication based on analysis of textures implemented on a FPGA

Among the most used biometric signals to set personal security permissions, taker increasingly importance biometric iris recognition based on their textures and images of blood vessels due to the rich in these two unique characteristics that are unique to each individual. This paper presents an implementation of an algorithm characterization and correlation of templates created for biometric authentication based on iris texture analysis programmed on a FPGA (Field Programmable Gate Array), authentication is based on processes like characterization methods based on frequency analysis of the sample, and frequency correlation to obtain the expected results of authentication.

System of acquisition and processing of images of dynamic speckle

In this paper we show the design and implementation of a system to capture and analysis of dynamic speckle. The device consists of a USB camera, an isolated system lights for imaging, a laser pointer 633 nm 10 mw as coherent light source, a diffuser and a laptop for processing video. The equipment enables the acquisition and storage of video, also calculated of different descriptors of statistical analysis (vector global accumulation of activity, activity matrix accumulation, cross-correlation vector, autocorrelation coefficient, matrix Fujji etc.). The equipment is designed so that it can be taken directly to the site where the sample for biological study and is currently being used in research projects within the group.