This paper presents an algorithm for fingerprint image restoration using Digital Reaction-Diffusion System (DRDS). The DRDS is a model of a discrete-time discrete-space nonlinear reaction-diffusion dynamical system, which is useful for generating biological textures, patterns and structures. This paper focuses on the design of a fingerprint restoration algorithm that combines (i) a ridge orientation estimation technique using an iterative coarse-to-fine processing strategy and (ii) an adaptive DRDS having a capability of enhancing low-quality fingerprint images using the estimated ridge orientation. The phase-only image matching technique is employed for evaluating the similarity between an original fingerprint image and a restored image. The proposed algorithm may be useful for person identification applications using fingerprint images.

A technique for the design of circular- and racetrack-shaped NRD guide ring resonators was developed based on the mode coupling theory. Besides the operating mode, a parasitic mode is generated at curved sections of the resonator as a result of the mode conversion. Resonance of the NRD guide ring resonator is derived by characteristic equations of the coupled modes and then employed in making the design diagrams, which are useful for determining the dimensions of the ring resonators. It is shown that the discrepancy between the experimental results and previous theory can be resolved by using the present theory. Low loss, small-sized ring resonators with curvature radii of less than 5.3 mm were fabricated at 60 GHz and a band rejection performance of more than 30 dB was observed. Moreover, a procedure for the design of the channel dropping filter was developed and a 2-pole filter, which has great advantages such as a low insertion loss of 1.2 dB and a compact size smaller than that of a golf ball, was successfully developed by using two racetrack-shaped ring resonators.

This paper presents a Field-Programmable Digital Filter (FPDF) IC that employs carry-propagation-free redundant arithmetic algorithms for faster computation and multiple-valued current-mode circuit technology for high-density low-power implementation. The original contribution of this paper is to evaluate, through actual chip fabrication, the potential impact of multiple-valued current-mode circuit technology on the reduction of hardware complexity required for DSP-oriented programmable ICs. The prototype FPDF fabrication with 0.6 µm CMOS technology demonstrates that the chip area and power consumption can be reduced to 41% and 71%, respectively, compared with the standard binary logic implementation.

In this paper, we propose a simple method to find the optimal rational function, with a fixed denominator, which minimizes an integral of polynomially weighted squared error to given analytic function. Firstly, we present a generalization of the Walsh's theorem. By using the knowledge on the zeros of the fixed denominator, this theorem characterizes the optimal rational function with a system of linear equations on the coefficients of its numerator polynomial. Moreover when the analytic function is specially given as a polynomial, we show that the optimal numerator can be derived without using any numerical integration or any root finding technique. Numerical examples demonstrate the practical applicability of the proposed method.

In this paper, we propose a new configuration to implement transversal filters with negligible temperature sensitivity and low cost. These microwave filters are based on uniform fibre Bragg gratings as slicing elements of a broadband optical source. By using a tapered fibre Bragg grating as a delay line, we show that the temperature effects are the same over each component of the RF-filter. Therefore, it is possible a total cancellation of the thermal effects. The performance of these filters is compared to previous techniques, such as a laser array approach.

In this paper, a novel flexible photonic microwave filter architecture based on the use of laser arrays and the periodicity of N N arrayed waveguide gratings (AWG) optical response is proposed. Independent filter response coarse and fine tuning as well as reshaping of each transversal filter response have been experimentally demonstrated showing an excellent agreement with theory.

This article presents a three-step method for designing linear phase FIR filters with signed-powers-of-two (SPT) coefficients. In Step one, a prototype optimal FIR filter is designed by the Remez exchange algorithm. In Step two, a scaling factor is selected by employing simple ad-hoc rules. In Step three, each coefficient of the prototype filter is scaled by the scaling factor and is quantized coarsely as the canonic-signed-digit (CSD) representation. Then, a mixed-integer-linear-programming (MILP) algorithm is applied to three least significant digits (LSDs) of the filter's coefficients to reduce the number of SPT terms. Design examples demonstrate that the proposed algorithm is able to produce linear phase fixed-point FIR filters using fewer SPT terms than the existing methods under the same normalized peak ripple magnitude (NPRM) specification.

It is widely known that the family of projection filters includes the generalized inverse filter, and that the family of parametric projection filters includes parametric generalized projection filters. However, relations between the family of parametric projection filters and constrained least squares filters are not sufficiently clarified. In this paper, we consider relations between parameter estimation and image restoration by these families. As a result, we show that the restored image by the family of parametric projection filters is a maximum penalized likelihood estimator, and that it agrees with the restored image by constrained least squares filter under some suitable conditions.

In general, the attenuation characteristics of band-pass filters can be improved by generating attenuation poles in the stop band. In this paper, a design method for a planar band-pass filter with attenuation poles based on a half-wavelength resonator is proposed. According to this design, the attenuation poles can be obtained at any desired frequency by means of coupling structures. Two kinds of filter with the characteristics of steep skirt and wide stop-band were designed and fabricated with the result that the validity of the design method was demonstrated. Therefore, a filter with excellent attenuation characteristics for various applications can be achieved.

The transfer characteristic of an integrator is affected by excess-phase shift caused by the parasitic capacitance. The phase compensation is obtained by introducing zeros to generate phase lead. This paper proposes a phase compensation technique for the differential signal input integrator. The proposed technique is employing feedforward signal current source. The fifth-order leapfrog Chebyshev low-pass filter with 0.5 dB passband ripple is designed using the integrator with the proposed phase compensation. Further, an autotuning phase compensation system using the proposed technique is realized by applying a PLL system. The effectiveness of the proposed technique is confirmed by PSPICE simulation. The simulation results of the integrator with the proposed phase compensation shows that excess-phase cancellation is obtained at various unity gain frequencies. The accurate filter characteristic of the fifth-order leapfrog filter is obtained by using the autotuning phase compensation system. The passband of the filter is improved over wide range of frequencies. The proposed technique is suitable for low voltage application.

This article addresses the problem of designing and implementing multigigabit post-detection filters for application in optical communication systems using optical soliton pulses. The designed filters have the main advantages of full integration, electrically adjustable frequency response and active input and output impedance match.

This paper describes the outline of the active noise control system and the adaptive signal processing used in the practical systems. Focus is on the adaptive signal processing and algorithms which are widely used in many applications. Some variations in the algorithms for improving the control effect and for reducing the amount of calculation are also shown. Additionally, the limitations and some design guide are shown with the results of the numerical simulations.

A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

This letter proposes a new approach for feature extraction using steerable filters. This approach is based on the concept of orientation-energy histogram which yields the local direction of dominant orientation. The testing is carried out using a training set of 1000 and a set of 300 unknown 40 40 hand-written digits. As a result of the simulations, 92% correct recognition is provided.

This paper presents a novel approach to water pollution detection from remotely sensed low-platform mounted visible band camera images. We examine the feasibility of unsupervised segmentation for slick (oily spills on the water surface) region labelling. Adaptive and non adaptive filtering is combined with density modeling of the obtained textural features. A particular effort is concentrated on the textural feature extraction from raw intensity images using filter banks and adaptive feature extraction from the obtained output coefficients. Segmentation in the extracted feature space is achieved using Gaussian mixture models (GMM).

A new approach to design variable IIR digital filters by using a cascade of N identical individual filters of any order n is proposed in this paper. First, the approximation method for lowpass filter specifications is outlined, then the general limitations of the new method are investigated and a compact formula is derived. Next, the limitations for the main canonic approximations (Butterworth, Chebyshev and Elliptic) are investigated and compared and convenient expressions for design and evaluation are obtained. New first- and second-order filter sections, permitting very easy tuning of the cutoff frequency by recalculating and reprogramming of a single multiplier coefficient value, are developed and the design and tuning strategies for highpass, bandpass and bandstop filters are proposed. Finally design examples are given and the sound superiority of the new method compared to other known is demonstrated experimentally.

This paper presents a digital reaction-diffusion system (DRDS)--a model of a discrete-time discrete-space reaction-diffusion dynamical system--for designing new image processing algorithms inspired by biological pattern formation phenomena. The original idea is based on the Turing's model of pattern formation which is widely known in mathematical biology. We first show that the Turing's morphogenesis can be understood by analyzing the pattern forming property of the DRDS within the framework of multidimensional digital signal processing theory. This paper also describes the design of an adaptive DRDS for image processing tasks, such as enhancement and restoration of fingerprint images.

For low-complexity linear-phase FIR digital filters which have coefficients expressed as canonic signed digit (CSD) code, a design method to impose power-of-two DC gain is proposed. Output signal level can easily be compensated to that of input so that cascading many stages do not cause any gain errors, which are harmful in, for example, high precision measurement systems. The design is formulated as an optimization problem with magnitude response constraints. The integer linear programming modified for CSD codes is solved by the branch and bound method. The design example shows the effectiveness of the obtained filter in comparison with existing CSD filters. Also, an evaluation method for the area to implement the filter into field programmable gate array (FPGA) is proposed. The implementation example shows that the minimum critical path is obtained with only a little increase in the die area.

A new approach for extracting significant characteristic within speech signal for distinct speaker is presented. Based on the multiresolution property of wavelet transform, quadrature mirror filters (QMFs) derived by Daubechies is used to decompose the input signal into varied frequency channels. Owning to the uncorrelation property of each resolution derived from QMFs, Linear Predict Coding Cepstrum (LPCC) of lower frequency region and entropy information of higher frequency region for each decomposition process are calculated as the speech feature vectors. In addition, a hard thresholding technique for lower resolution in each decomposition process is also used to remove the effect of noise interference. The experimental result shows that by using this mechanism, not only effectively reduce the effect of noise inference but improve the recognition rate. The proposed feature extraction algorithm is evaluated on MAT telephone speech database for Text-Independent speaker identification using vector quantization (VQ). Some popular existing methods are also evaluated for comparison in this paper. Experimental results show that the performance of the proposed method is more effective and robust than that of the other existing methods. For 80 speakers and 2 seconds utterance, the identification rate is 98.52%. In addition, the performance of our method is very satisfactory even at low SNR.

A framework is proposed for segmenting image textures by using Gabor filters to detect boundaries between adjacent textured regions. By performing a multi-channel filtering of the input image with a small set of adaptively selected Gabor filters, tuned to underlying textures, feature images are obtained. To reduce the variance of the filter output for better texture boundary detection, a Gaussian post-filter is applied to the Gabor filter response over each channel. Significant local variations in each channel response are detected using a gradient operator, and combined through channel grouping to produce the texture gradient. A subsequent post-processing produces expected texture boundaries. The effectiveness of the proposed technique is demonstrated through experiments on synthetic and natural textures.