Sayaka Shiota

An encryption-then-compression system for JPEG standard

In many multimedia applications, image encryption has to be conducted prior to image compression. This paper proposes an Encryption-then-Compression system using a JPEG-friendly perceptual encryption method, which enables to be conducted prior to JPEG compression. The proposed encryption method can provides approximately the same compression performance as that of JPEG compression without any encryption, where both gray scale images and color ones are considered. It is also shown that the proposed system consists of four block-based encryption steps, and provide a reasonably high level of security. Most of conventional perceptual encryption methods have not been designed for international compression standards, but this paper focuses on applying the JPEG standard, as one of the most widely used image compression standards.

Fast inverse tone mapping with Reinhard's global operator

This paper proposes a novel inverse TMO, which enables to generate HDR images from LDR ones, not only without using any specific parameters but also at low computing costs. Furthermore, the inverse TMO has a new characteristic when an LDR image is mapped from an HDR one by Reinhards global operator. In the case, the HDR image reconstructed by the proposed method without parameters can be remapped into the same image as that remapped from an HDR one reconstructed with parameters. Experimental results show that the proposed inverse tone mapping (TM) operation can be carried out, while keeping better structural similarity and lower computing cost than conventional methods.

An Efficient Random Unitary Matrix for Biometric Template Protection

This paper proposes a new way to generate random unitary matrices for biometric template protection. It is well known that the unitary transform-based template protection that is a class of cancelable biometrics systems, has some desirable properties such as being applicable to l2-norm minimization problems. However, its performance and effectiveness depend on the variety of a unitary matrix. The aim of this paper is to generate an effective random unitary matrix and evaluate the effectiveness in terms of security, recognition performance and the complexity of the recognition system. The proposed random matrix consists of a random permutation matrix and a unitary matrix in which all elements have fixed values as the discrete Fourier transform(DFT). It is also applied to face recognition experiments to demonstrate the effectiveness.

Reinhard's global operator based inverse tone mapping with one parameter

This paper proposes a new inverse tone mapping operator (TMO) with only one parameter. The proposed inverse TMO is based on Reinhards global operator which is a well-known TMO. Inverse TM operations have two applications: generating an HDR image from an existing LDR one, and reconstructing an original HDR image from the mapped LDR image. In this paper, we focus on the latter application and the proposed method can produce an HDR image that has high image quality. In the latter application, two parameters used in Reinhards TMO, i.e. the key value α regarding brightness of a mapped LDR one and the geometric mean Lw of an original HDR one, are generally required for carrying out the Reinhard based inverse_TMO. In this paper, we show that it is possible to estimate Lw from α under some conditions, so that a new inverse TMO with one parameter is proposed. Experimental results show that the proposed method outperforms conventional ones for the latter application, in terms of high image quality and low computing cost.

Ensemble based speaker verification using adapted score fusion in noisy reverberant environments

This paper proposes an ensemble based automatic speaker recognition (ASV) using adapted score fusion in noisy reverberant environment. It is well known that background noise and reverberation affect the performance of the ASV systems. Various techniques have been reported to improve the robustness against noise and reverberation, and an ensemble based method is one of the effective techniques in the noisy environment. The ensemble based method uses a combination of several weak learners to achieve higher performance than a single learner method. However, since the performance is depended on the fusion weights, the adequate weight estimation method is required. The proposed weight estimation method is based a supervised adaptation and the evolutionary update algorithm. The QUT-NOISE-SRE protocol, which has been published recently, is used for simulating the reverberation of the clean speech in our experiments. The experimental results report the characteristics of the QUT-NOISE-SRE protocol and the effectiveness of the proposed method in noisy reverberant environment.

Voice livness detection based on pop-noise detector with phoneme information for speaker verification

This paper proposes a pop-noise detector using phoneme information for a voice liveness detection (VLD) framework. In recent years, spoofing attacks (e.g., reply, speech synthesis, and voice conversion) have become a serious problem against speaker verification systems. Some techniques have been proposed to protect the speaker verification systems from these spoofing attacks. The VLD framework has been proposed as one of fundamental solutions. The VLD framework identifies that an input sample is uttered by an actual human or played by a loudspeaker. To realize the VLD framework, pop-noise detection methods have been proposed and these methods perform well as the VLD module. However, since pop-noise is a common distortion in speech that occurs when a speaker’s breath reaches a microphone, the phenomenon of pop-noise is able to be occurred by winds or attackers arbitrary. It is one problem of the pop-noise detection methods. In order to improve the robustness of the pop-noise detection methods, this paper p...

Image invisibility assessment for visually encrypted images

A variety of perceptual encryption schemes have been studied to generate visually encrypted images for protecting visual secrecy and privacy while supporting ongoing innovation and growth in the applications of digital imagery. However, typical image quality metrics such as PSNR and SSIM are not suitable to evaluate the invisibility of visually encrypted images. To overcome this issue, this paper proposes a novel full-reference invisibility index, referred to as the Triple feature similarity index (TFSI), for visually encrypted images. The TFSI is computed through four steps: 1) edge extraction as preprocessing, 2) extracting the Triple feature based on the Trace transform, 3) normalization of resolution, and 4) TFSI is computed between the reference and visually encrypted images. Experimental results show that the TFSI measures the invisibility of visually encrypted images.