Izumi Ito

DCT Sign-Only Correlation with Application to Image Matching and the Relationship with Phase-Only Correlation

A close relationship between the sign information of discrete cosine transform (DCT) coefficients and the phase term of discrete Fourier transform coefficient is explained. From this relationship, the DCT sign-only correlation is proposed and its relationship with the phase-only correlation (POC) is considered. As a result, the proposed correlation can be applied to applications based on the POC, and also provide a theoretical explanation of target image search and retrieval using the sign information of DCT.

A new class of image registration for guaranteeing secure data management

We propose a method of image registration between scrambled images in order to guarantee the secure data management. This method uses either phase-only correlation or DCT sign phase correlation for the registration. Correlation and registration values between images are directly estimated in the scrambled domain. Information in each image is protected and the relative relation with other images is held by synchronizing scrambling. As a result, the proposed method has no effect on registration accuracy. Translation estimation experiments are performed to show the appropriateness and the effectiveness of the proposed method.

One-time key based phase scrambling for phase-only correlation between visually protected images

One-time key based phase scrambling is proposed for privacy-protected image matching. The image matching is performed using invisible templates that are protected by phase scrambling. A key for phase scrambling is not required for the image matching, and the key can even be discarded after scrambling if the template does not need to be reconstructed. Theoretical analyses are presented to provide guidelines for designing key parameters that affect the visual effect and image matching. Experimental results demonstrate the effectiveness and appropriateness of the proposed method.

Phase scrambling for blind image matching

We propose a phase-scrambling method for blind image matching, which is a direct image matching between invisible images. The phase scrambling is motivated by visual protection of images and prevention of illegal image matching. Phase-only correlation (POC) can be directly applied to images protected by the proposed phase scrambling in order to estimate similarity and translation between images. POC with synchronized scrambling provides blind image matching, in which phase scrambling does not affect the accuracy of POC. The effect of visual protection and prevention of illegal image matching is evaluated through simulations to show the effectiveness of the proposed method.

Multiple-peak model fitting function for DCT sign phase correlation with non-integer shift precision

We propose two fitting functions for shift estimation using discrete cosine transform sign phase correlation (DCT-SPC) with non-integer accuracy. The DCT-SPC can be used in order to estimate the shift values and the similarity between two signals. However, the estimated shift values are limited to integer numbers. The proposed fitting functions enable the DCT-SPC to estimate the non-integer shift values using only the sign of the DCT coefficients. The multiple-peak model in the proposed fitting functions provides more accurate values than other models. Simulations are presented to demonstrate the effectiveness of the proposed fitting functions.

Phase-only correlation based matching in scrambled domain for preventing illegal matching

We herein propose an image matching in the scrambled domain for preventing illegal image matching, which is defined as a malicious and intentional act conducted in order to deduce the content of images. The phase of discrete Fourier transform (DFT) coefficients of images is scrambled for visual protection. In addition, the magnitude of DFT coefficients is scrambled for preventing illegal image matching. Phase-only correlation (POC) or phase correlation can be applied directly to images in the scrambled domain for alignment and similarity. The accuracy of POC in the scrambled domain is the same as that in the non-scrambled domain. Simulations are presented to confirm the appropriateness and effectiveness of the proposed scrambling.

A computing method of double linear correlation for mirror image matching

A computing method of double linear correlation is proposed in order to estimate the location in which the part of an image matches another image even if one of the images is mirrored across the vertical, horizontal, or both axes. 1-D double linear correlation (DLC) is extended to 2-D DLC. The reduction of the number of zero-padding is considered. The computational complexity of the proposed method is lower than that of an FFT approach by more than 50% the number of operations on real numbers.

A new technique of non-iterative super-resolution without boundary distortion

We propose a new technique of non-iterative super-resolution image reconstruction. A closed form solution to reconstruction is derived in the discrete cosine transform (DCT) domain from a MAP-based cost functional. An average image is used in order to avoid iterative operations. Symmetric convolution with appropriate types of DCT suppresses boundary distortion. Experimental results demonstrate the effectiveness of the proposed technique.

Phase Scrambling for Image Matching in the Scrambled Domain

In recent years, signal matching has been required in many fields. A number of matching methods have been developed, and an appropriate method should be selected for each application in order to obtain the desired performance (1)(2). Phase-only correlation (POC), phase correlation or PHAse Transform (PHAT) (3)-(17), which is referred to herein as POC, is a phase-based correlation that is used for various applications, such as delay estimation (3)(4), motion estimation (5), registration (6)(7), video detection (8)(9), and biometrics authentication (10)(11). Phase-only correlation with Fourier transform was developed as PHAT in sound/sonar processing literature (3), and POC with discrete Fourier transform was proposed by Kuglin and Hines (12). The concept of POC is based on the fact that the information related to the displacement of two signals resides in the phase of the cross spectrum. Combining POC with various techniques, such as interpolation and curve fitting, provides highly accurate estimation (13)-(17). In special cases, the normalized cross spectrum corresponds to the product of the signs of discrete cosine transform (DCT) coefficients. Previously, we derived this relationship mathematically and proposed DCT sign phase correlation (DCT-SPC) based on this relationship (18). DCT-SPC is a phase-based correlation and has properties that are similar to those of POC. Images, particularly in the fields of biometrics, medicine, and surveillance camera require extreme security in order to avoid the risk of identity theft and invasion of privacy (19). Generally, encrypting and scrambling are used to protect information (20) (21). However, these protected images require decrypting or descrambling before image matching. In other words, neither POC nor DCT-SPC can be directly applied to conventional encrypted and scrambled images. Based on privacy concerns, secure multi-party techniques were applied to vision algorithms such as Blind Vision in (22). However, in (22), neither the registration nor the estimation of the geometric relationship between two images was discussed. In this chapter, for POC and DCT-SPC, we present phase-scrambled signals and a matching method that can be directly applied to phase-scrambled signals without descrambling. The presented methods are motivated by secure data management. The phase scrambling distorts only the phase information, which contains significant information of signals. Phase scrambling protects against the exposure of the information in the signal. Synchronized phase scrambling yields the relationship between non-scrambled signals. Therefore, POC and DCTSPC can be directly applied to phase-scrambled signals. Moreover, the presented scrambling 2

Translational displacement estimation with subpixel accuracy of DCT-sign phase correlation

The accuracy of subpixel estimation of Discrete Cosine Transform (DCT) -sign phase correlation (-SPC) is presented using real images involved by actual movement. So far, the accuracy had been reported just using simulated images. Using real images and two types of simulated images, we evaluate the performance with subpixel accuracy of DCT-SPC with curve fitting compared to phase correlation with curve fitting. For real images captured by a commercial-off-the-shelf product camera, the error of estimated value with subpixel accuracy of DCT-SPC with curve fitting is lower than that of phase correlation with curve fitting, although DCT-SPC uses only the signs of DCT coefficients, while phase correlation uses the phase term with complex numbers.