With the distributed data mining technique having been widely used in a variety of fields, the privacy preserving issue of sensitive data has attracted more and more attention in recent years. Our major concern over privacy preserving in distributed data mining is the accuracy of the data mining results while privacy preserving is ensured. Corresponding to the horizontally partitioned data, this paper presents a new hybrid algorithm for privacy preserving distributed data mining. The main idea of the algorithm is to combine the method of random orthogonal matrix transformation with the proposed secure multi-party protocol of matrix product to achieve zero loss of accuracy in most data mining implementations.

In this paper, a design method of two-dimensional (2-D) orthogonal symmetric wavelets is proposed by using a lattice structure for multi-dimensional (M-D) linear-phase paraunitary filter banks (LPPUFB), which the authors have proposed as a previous work and then modified by Lu Gan et al. The derivation process for the constraints on the second-order vanishing moments is shown and some design examples obtained through optimization with the constraints are exemplified. In order to verify the significance of the constraints, some experimental results are shown for Lena and Barbara image.

As digital television transmission is becoming ubiquitous, a method that can remotely monitor the quality of the final and intermediate pictures is urgently needed. In particular, the case where standards conversion is included in the transmission chain is a serious issue as the input and output cannot simply be compared. This letter proposes a novel method to solve this issue. The combination of skipping fields/pixels and the previously proposed SSSWHT-RR method, using the information of correlation coefficients and variance of the picture, achieves accurate detection of picture failure.

This paper proposes a high-resolution CMOS image sensor, which has Hadamard transform function. This Hadamard transform circuit consists of two base generators, an array of pixel circuits, and analog-to-digital converters. In spite of simple composition, a base generator outputs a variety of bases, a pixel circuit calculates a two-dimensional base from one-dimensional bases and outputs values to common line for current addition, and analog-to-digital converter converts current value to digital value and stabilize a common line voltage for elimination of parasitic capacitance. We simulated these circuit elements and optimized using SPICE. Basic operations of this Hadamard transform circuit are also confirmed by simulation. A 256 256 pixel test chip was designed in 4.73 mm 4.73 mm area with 0.35 µm CMOS technology. A fill factor of this chip is 42% and dynamic range is 55.6 [dB]. Functions of this chip are Hadamard transform, Harr transform, projection, obtaining center of gravity, and so on.

Watermarking methods that employ orthogonal transformations are very robust against non-geometrical modifications such as lossy compression, but attaining robustness against image translation or cropping is difficult. This report describes a watermarking method that increases robustness against geometrical modifications such as image translation and cropping by embedding watermark data in the frequency component of an image and detecting that data by considering the phase difference of the coefficients that results from translation of the image. Experimental results demonstrate the robustness of this method against both non-geometrical image changes and image translation and cropping.

In this paper, comparison of various orthogonal transforms in Wiener filtering is discussed. The study involves the family of discrete orthogonal transforms called Complex Hadamard Transform, which has been recently introduced by the same authors. Basic definitions, properties and transformation kernel of Complex Hadamard Transform are also shown.

This paper establishes a general relation between the two-dimensional Least Mean Square (2-D LMS) algorithm and 2-D discrete orthogonal transforms. It is shown that the 2-D LMS algorithm can be used to compute the forward as well as the inverse 2-D orthogonal transforms in general for any input by suitable choice of the adaptation speed. Simulations are presented to verify the general relationship results.

The relation between computing part of the FFT spectrum and the so-called generalized FFT (GFFT) is clarified, leading to a new algorithm for performing partial FFTs. The method can be applied when only part of the output is required or when the input data sequence contains many zeros. Such cases arize for example in decimation and interpolation and also in computing linear convolutions. The technique consists of decomposing the DFT into several generalized DFTs. Efficient algorithms for these generalized DFTs exist. The computational complexity of the new approach is roughly equal to the complexity of previous techniques, but the structure is superior, because only one type of butterfly is used and a few lines of code are sufficient. The theoretical properties of the GDFT are given. The case of multidimensional signals, defined on arbitrary sampling lattices is also considered.

It is known that the resolution conversion based on orthogonal transform has a problem that is difference of luminance between the converted image and the original. In this paper, the scale factor of the system employing various orthogonal transforms is generally formulated by considering the DC gain, and the condition of alias free for DC component is indicated. If the condition is satisfied, then the scale factor is determined by only the basis functions.