A new simultaneous compression and encryption method for images suitable to recognize form by optical correlation

Abstract

In some recognition form applications (which require multiple images: facial identification or sign-language), many images should be transmitted or stored. This requires the use of communication systems with a good security level (encryption) and an acceptable transmission rate (compression rate). In the literature, several encryption and compression techniques can be found. In order to use optical correlation, encryption and compression techniques cannot be deployed independently and in a cascade manner. Otherwise, our system will suffer from two major problems. In fact, we cannot simply use these techniques in a cascade manner without considering the impact of one technique over another. Secondly, a standard compression can affect the correlation decision, because the correlation is sensitive to the loss of information. To solve both problems, we developed a new technique to simultaneously compress & encrypt multiple images using a BPOF optimized filter. The main idea of our approach consists in multiplexing the spectrums of different transformed images by a Discrete Cosine Transform (DCT). To this end, the spectral plane should be divided into several areas and each of them corresponds to the spectrum of one image. On the other hand, Encryption is achieved using the multiplexing, a specific rotation functions, biometric encryption keys and random phase keys. A random phase key is widely used in optical encryption approaches. Finally, many simulations have been conducted. Obtained results corroborate the good performance of our approach. We should also mention that the recording of the multiplexed and encrypted spectra is optimized using an adapted quantification technique to improve the overall compression rate.

A fast, efficiency-preserving system for simultaneous compression & encryption

“…Several authors have demonstrated that significant compression of encrypted data can be obtained in the general case [2,[7][8][9][10][11][12][13]. In specific situations, the authors claim that the same code rate is achievable by encrypting before compressing as compressing before encrypting.…”

Numerical implementation of the multiple image optical compression and encryption technique

“…Understanding and optimizing optical processing of information techniques is one of the fundamental issues in communication and information technologies [1][2][3][4][5][6][7][8] . Several methods based on spatial filtering have been used to encrypt images.…”

Cipherstream covering for secure data compression

“…Significant compression of encrypted data occurs in some cases [4][5][6][7][8][9][10][11][12], and in specific situations, encrypting before compressing produces the same code rate as compressing before encrypting. In the special case of compression of a Gaussian distributed source with a mean-squared error fidelity criterion, the encrypted file compresses to the same entropy rate as the original source [13].This applies to both lossless and lossy compression, but not, in general, to data that deviates from Gaussian source conditions.…”