A Cascaded Iterative Fourier Transform Algorithm For Optical Security Applications

A cascaded iterative Fourier transform (CIFT) algorithm is presented for optical security applications. Two phase-masks are designed and located in the input and the Fourier domains of a 4-f correlator respectively, in order to implement the optical encryption or authenticity verification. Compared with previous methods, the proposed algorithm employs an improved searching strategy: modifying the phase-distributions of both masks synchronously as well as enlarging the searching space. Computer simulations show that the algorithm results in much faster convergence and better image quality for the recovered image. Each of these masks is assigned to different person. Therefore, the decrypted image can be obtained only when all these masks are under authorization. This key-assignment strategy may reduce the risk of being intruded.Comment: 18 pages, 4 figures, 2 tables. submitted to Opti

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.Iterative Korrelation zur Mustererkennung von Objekten in komplexen Szene

DESEMPEÑO DE UN CORRELADOR HIBRIDO DE TRANSFORMACION CONJUNTA A UNA RAPIDEZ DE PROCESAMIENTO MAYOR A LA VELOCIDAD DE VIDEO,CON UN SOLO PROCESADOR DIGITAL

En este trabajo un correlador híbrido de transformación conjunta JTC de bajo costo que usa de manera complementaria las propiedades ópticas y las electrónicas, es implementado experimentalmente. Este correlador resuelve los mayores inconvenientes de un JTC óptico convencional. El JTC híbrido usa un único procesador digital de señales DSP para procesar la densidad espectral de energía conjunta JPS que es obtenida por vía óptica. La JPS de la escena y la referencia, colocadas en un modulador espacial de luz que actúa como plano de entrada, es obtenida en el plano focal imagen del procesador óptico. La adquisición digital de la JPS se hace mediante un sensor CCD que actúa como entrada al DSP. La reducción del pico central de energía de la JPS se realiza mediante un filtro óptico apodizante justo antes del sensor. Finalmente, el DSP realiza una transformación de Fourier digital de la JPS, controla todo el proceso y calcula las métricas de desempeño del correlador. Los requerimientos computacionales se reducen significativamente con la simetría hermítica de la transformada de Fourier realizada mediante el DSP para imágenes reales, esto es, que su velocidad de procesamiento lo hace hábil también para detectar objetos en escenas móviles

Reconnaissance Biométrique par Fusion Multimodale de Visages

Biometric systems are considered to be one of the most effective methods of protecting and securing private or public life against all types of theft. Facial recognition is one of the most widely used methods, not because it is the most efficient and reliable, but rather because it is natural and non-intrusive and relatively accepted compared to other biometrics such as fingerprint and iris. The goal of developing biometric applications, such as facial recognition, has recently become important in smart cities. Over the past decades, many techniques, the applications of which include videoconferencing systems, facial reconstruction, security, etc. proposed to recognize a face in a 2D or 3D image. Generally, the change in lighting, variations in pose and facial expressions make 2D facial recognition less than reliable. However, 3D models may be able to overcome these constraints, except that most 3D facial recognition methods still treat the human face as a rigid object. This means that these methods are not able to handle facial expressions. In this thesis, we propose a new approach for automatic face verification by encoding the local information of 2D and 3D facial images as a high order tensor. First, the histograms of two local multiscale descriptors (LPQ and BSIF) are used to characterize both 2D and 3D facial images. Next, a tensor-based facial representation is designed to combine all the features extracted from 2D and 3D faces. Moreover, to improve the discrimination of the proposed tensor face representation, we used two multilinear subspace methods (MWPCA and MDA combined with WCCN). In addition, the WCCN technique is applied to face tensors to reduce the effect of intra-class directions using a normalization transform, as well as to improve the discriminating power of MDA. Our experiments were carried out on the three largest databases: FRGC v2.0, Bosphorus and CASIA 3D under different facial expressions, variations in pose and occlusions. The experimental results have shown the superiority of the proposed approach in terms of verification rate compared to the recent state-of-the-art method

Properties and processing applications of photoreactive BSO

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN016580 / BLDSC - British Library Document Supply CentreGBUnited Kingdo