In this letter, we present a method for automatic mura detection for display film using the efficient decision of cut-off frequency with DCT and mask filtering with wavelet transform. First, the background image including reflected light is estimated using DCT with adaptive cut-off frequency, and DWT is applied to background-removed images for generating mura mask. Then, a mura mask is generated by separating low-frequency noise in the approximation coefficients. Lastly, mura is detected by applying mura mask filtering to the detail coefficients. According to the comparison by Semu index, the results from the proposed method are superior to those from the existing methods. This indicates that the proposed method is high in reliability.

This paper presents a filtering method for efficient face image retrieval over large volume of face databases. The proposed method employs a new face image descriptor, called a cell-orientation vector (COV). It has a simple form: a 72-dimensional vector of integers from 0 to 8. Despite of its simplicity, it achieves high accuracy and efficiency. Our experimental results show that the proposed method based on COVs provides better performance than a recent approach based on identity-based quantization in terms of both accuracy and efficiency.

We introduce a MIMO channel estimation method that exploits the channel's spatiotemporal correlation without the aid of a priori channel statistical information. A simplified Gauss-Markov model that has fewer parameters to be estimated is presented for the Kalman filter. In order to obtain statistical parameters on the time evolution of the channel, considering that the time evolution is a latent statistical variable, the expectation-maximization (EM) algorithm is applied for accurate estimation. Numerical simulations reveal that the proposed method is able to enhance estimation capability by exploiting spatiotemporal correlations, and the method works well even if the forgetting factor is small.

In this letter, we propose a new intra-field deinterlacing algorithm based on an edge dependent weighted filter (EDWF). The proposed algorithm consists of three steps: 1) calculating the gradients of three directions (45°, 90°, and 135°) in the local working window; 2) achieving the weights of the neighboring pixels by exploiting the edge information in the pixel gradients; 3) interpolating the missing pixel using the proposed EDWF interpolator. Compared with existing deinterlacing methods on different images and video sequences, the proposed algorithm improves the peak signal-to-noise-ratio (PSNR) while achieving better subjective quality.

This paper proposes a novel scheme for sequential orthogonal frequency division multiplexing channel estimation on the receiver side.The scheme comprises two methods: one improves estimation accuracy and the other reduces computational complexity. Based on a state-space model, the first method appropriately considers frequency correlation in an approach that derives a narrow-band channel gain for multiple pilot subcarriers; such consideration of frequency correlation leads to an averaging effect in the frequency domain. The second method is based on the first one and forces the observation matrix into a sparse bidiagonal matrix in order to decrease the number of mathematical processes. The proposed scheme is verified by numerical analysis.

In digital cinema, an image goes through many types of processes like scanning, mastering, and digital intermediate. Among them, the digital intermediate process plays a central role because it determines the final color of an image. It edits and changes the colors of the images. However, some color distortions such as color bleeding are generated when editing and changing local colors in an image. In this paper, local color improvement for digital intermediate is proposed based on color transfer. Our method is simple and efficient color improvement that does not requires neither precise image segmentation nor feature matching. To prevent color distortions, a modified color influence map is proposed with color categories. First, the source image is roughly segmented using a color category map, which groups similar colors in color space. Second, the color influence map is modified by assigning different weights to the lightness and chroma components. Lastly, the modified color influence map and color category map filtered with anisotropic diffusion are combined. Experimental results show that the proposed method produces less color distortion in the resulting image.

A new technology for video frame rate up-conversion (FRUC) is presented by combining a median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to obtain a motion vector. Then, the OD method is used to refine the MV in the occlusion region. When occlusion occurs, median filtering is applied. Otherwise, bidirectional motion compensated interpolation (BDMC) is applied to create the interpolated frames. The experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain in the PSNR (Peak Signal to Noise Ratio) is always better than the other methods in the Full HD test sequences.

For a large-sized touch screen, we designed and evaluated a real-time touch microarchitecture using a field-programmable gate array (FPGA). A high-speed hardware accelerator based on a parallel touch algorithm is suggested and implemented in this letter. The touch controller also has a timing control unit and an analog digital convert (ADC) control unit for analog touch sensing circuits. Measurement results of processing time showed that the touch controller with its proposed microarchitecture is five times faster than the 32-bit reduced instruction set computer (RISC) processor without the touch accelerator.

In this paper, we propose a new structure for a compact matched filter bank for a mutually orthogonal zero-correlation zone (MO-ZCZ) sequence set consisting of ternary sequence pairs obtained by Hadamard and binary ZCZ sequence sets; this construction reduces the number of two-input adders and delay elements. The matched filter banks are implemented on a field-programmable gate array (FPGA) with 51,840 logic elements (LEs). The proposed matched filter bank for an MO-ZCZ sequence set of length 160 can be constructed by a circuit size that is about 8.6% that of a conventional matched filter bank.

This study proposes a novel method for evaluating the transmission characteristics of a three-phase filter using the “Fortescue-mode S-parameters,” which are S-parameters whose variables are transformed into symmetrical coordinates (i.e., zero-/positive-/negative-phase sequences). The behavior of the filter under three-phase current, including its non-symmetry, can be represented by these S-parameters, without regard to frequency. This paper also describes a methodology for creating modal equivalent circuits that reflect Fortescue-mode S-parameters allowing the effects of circuit components on filter characteristics to be estimated. Thus, this method is useful not only for the measurement and evaluation but also for the analysis and design of a three-phase filter. In addition, the physical interpretation of asymmetrical/symmetrical insertion losses and the conversion method based on Fortescue-mode S-parameters are clarified.

Recently, design of sparse finite impulse response (FIR) digital filters has attracted much attention due to its ability to reduce the implementation cost. However, finding a filter with the fewest number of nonzero coefficients subject to prescribed frequency domain constraints is a rather difficult problem because of its non-convexity. In this paper, an algorithm based on binary particle swarm optimization (BPSO) is proposed, which successively thins the filter coefficients until no sparser solution can be obtained. The proposed algorithm is evaluated on a set of examples, and better results can be achieved than other existing algorithms.

This paper presents an adaptive feedback canceller (AFC) based on a pseudo affine projection (PAP) algorithm that can provide fast and stable adaptation to the time-varying environment. The proposed algorithm utilizes the adaptive linear prediction (LP) to obtain the LP coefficients of input signal model and the inverse gain filter (IGF) to alleviate the effect of compensation gain. As a result, when the input is model as an AR signal, the proposed algorithm satisfies the condition for having an almost unbiased estimatie of the feedback path and then its performance is relatively independent of the gain setting of hearing aids. Simulation results showed that the proposed algorithm is capable of obtaining unbaised feedback path estimates and high speech quality.

Dysarthric speech results from damage to the central nervous system involving the articulator, which can mainly be characterized by poor articulation due to irregular sub-glottal pressure, loudness bursts, phoneme elongation, and unexpected pauses during utterances. Since dysarthric speakers have physical disabilities due to the impairment of their nervous system, they cannot easily control electronic devices. For this reason, automatic speech recognition (ASR) can be a convenient interface for dysarthric speakers to control electronic devices. However, the performance of dysarthric ASR severely degrades when there is background noise. Thus, in this paper, we propose a noise reduction method that improves the performance of dysarthric ASR. The proposed method selectively applies either a Wiener filtering algorithm or a Kalman filtering algorithm according to the result of voiced or unvoiced classification. Then, the performance of the proposed method is compared to a conventional Wiener filtering method in terms of ASR accuracy.

In this paper, we propose a parameter estimation method using Volterra kernels for the nonlinear IIR filters, which are used for the linearization of closed-box loudspeaker systems. The nonlinear IIR filter, which originates from a mirror filter, employs nonlinear parameters of the loudspeaker system. Hence, it is very important to realize an appropriate estimation method for the nonlinear parameters to increase the compensation ability of nonlinear distortions. However, it is difficult to obtain exact nonlinear parameters using the conventional parameter estimation method for nonlinear IIR filter, which uses the displacement characteristic of the diaphragm. The conventional method has two problems. First, it requires the displacement characteristic of the diaphragm but it is difficult to measure such tiny displacements. Moreover, a laser displacement gauge is required as an extra measurement instrument. Second, it has a limitation in the excitation signal used to measure the displacement of the diaphragm. On the other hand, in the proposed estimation method for nonlinear IIR filter, the parameters are updated using simulated annealing (SA) according to the cost function that represents the amount of compensation and these procedures are repeated until a given iteration count. The amount of compensation is calculated through computer simulation in which Volterra kernels of a target loudspeaker system is utilized as the loudspeaker model and then the loudspeaker model is compensated by the nonlinear IIR filter with the present parameters. Hence, the proposed method requires only an ordinary microphone and can utilize any excitation signal to estimate the nonlinear parameters. Some experimental results demonstrate that the proposed method can estimate the parameters more accurately than the conventional estimation method.

In developing an automatic system of a single tooth length measurement on x-ray image, since a tooth shape is assumed to be straight and curve, an algorithm which can accurately deal with straight and curve is required. This paper proposes an automatic algorithm for measuring the length of single straight and curve teeth. In the algorithm consisting of control point determination, curve fitting, and length measurement, PCA is employed to find the first and second principle axes as vertical and horizontal ones of the tooth, and two terminal points of vertical axis and the junction of those axes are determined as three first-order control points. Signature is then used to find a peak representing tooth root apex as the forth control point. Bezier curve, Euclidean distance, and perspective transform are finally applied with determined four control points in curve fitting and tooth length measurement. In the experiment, comparing with the conventional PCA-based method, the average mean square error (MSE) of the line points plotted by the expert is reduced from 7.548 pixels to 4.714 pixels for tooth image type-I, whereas the average MSE value is reduced from 7.713 pixels and 7.877 pixels to 4.809 pixels and 5.253 pixels for left side and right side of tooth image type-H, respectively.

We have proposed an intruder detection method by using multiple-input multiple-output (MIMO) channels. Although the channel capacity for MIMO transmission is severely degraded in time-variant channels, we can take advantage of this feature in MIMO sensor applications. For MIMO sensors, the accurate estimation of channel state information (CSI) is essential. Moreover, the transceiver should be simplified from the viewpoint of saving power. Narrowband signals such as minimum shift keying (MSK) and offset quaternary phase shift keying signals are effective and are used in sensor network systems. However, because the timing and carrier offsets between the transmitter and receiver are relatively large compared to the symbol rate, accurate CSI estimation is impossible given the severe constraints imposed by the timing and carrier offsets. To solve this issue, a signal synchronization method for the CSI estimation using a narrowband MSK signal has been proposed. In this paper, we propose a new CSI estimation method for arbitrary amplitude and phase modulation schemes for the MIMO sensor. The key point of the proposed method is that control signals (unique words) are mapped so as not to pass through the origin of the complex I/Q plane. The estimation accuracy of the proposed method is evaluated via a computer simulation. Moreover, the basic performance by the proposed CSI estimation method is verified when considering intruder detection by MIMO sensor.

This paper proposes a compact three-mode H-shaped resonator bandpass filter fed by antiparallel coupled input/output lines. To investigate the resonant behavior of the H-shaped resonator, even/odd-mode resonance conditions of the resonator are first derived analytically. The multimode resonances of the H-shaped resonator filter are modeled by a multipath circuit formed with resonance paths. Moreover, a direct source/load coupling path is connected in parallel, of which the value shows a frequency dependency because of the antiparallel coupled feeding lines, thereby generating four transmission zeros (TZs) greater than the number of a theoretical limitation. The H-shaped resonator bandpass filter is synthesized, developed, and tested, showing a third-order passband response with four TZs located near the passband, and a wide stopband property.

With the advent of high speed links, online flow measurement for, e.g., flow round trip time (RTT), has become difficult due to the enormous demands placed on computational resources. Most existing measurement methods are designed to count the numbers of flows or sizes of flows, but we address the flow RTT measurement, which is an important QoS metric for network management and cannot be measured with existing measurement methods. We first adapt a standard Bloom Filter (BF) for the flow RTT distribution estimation. However, due to the existence of multipath routing and Syn flooding attacks, the standard BF does not perform well. We further design the double-deletion bloom filter (DDBF) scheme, which alleviates potential hash collisions of the standard BF by explicitly deleting used records and implicitly deleting out-of-date records. Because of these double deletion operations, the DDBF accurately estimates the RTT distribution of TCP flows with limited memory space, even with the appearance of multipath routing and Syn flooding attacks. Theoretical analysis indicates that the DDBF scheme achieves a higher accuracy with a constant and smaller amount of memory compared with the standard BF. In addition, we validate our scheme using real traces and demonstrate significant memory-savings without degrading accuracy.

In the theory of periodic gratings, there is no method to make up a numerical solution that satisfies the reciprocity so far. On the basis of the shadow theory, however, this paper proposes a new method to obtain a numerical solution that satisfies the reciprocity. The shadow thoery states that, by the reciprocity, the $m$th order scattering factor is an even function with respect to a symmetrical axis depending on the order $m$ of diffraction. However, a scattering factor obtained numerically becomes an even function only approximately, but not accurately. It can be decomposed to even and odd components, where an odd component represents an error with respect to the reciprocity and can be removed by the average filter. Using even components, a numerical solution that satisfies the reciprocity is obtained. Numerical examples are given for the diffraction of a transverse magnetic (TM) plane wave by a very rough periodic surface with perfect conductivity. It is then found that, by use of the average filter, the energy error is much reduced in some case.

The bilateral filter (BF) is a nonlinear and low-pass filter which can smooth an image while preserving detail structures. However, the filer is time consuming for real-time processing. In this paper, we bring forward a fresh idea that bilateral filtering can be accelerated by a multigrid (MG) scheme. Our method is based on the following two facts. a) The filtering result by a BF with a large kernel size on the original resolution can be approximated by applying a small kernel sized (3×3) version on the lower resolution many times on the premise of visual acceptance. Early work has shown that a BF can be viewed as nonlinear diffusion. The desired filtering result is actually an intermediate status of the diffusion process. b) Iterative linear equation techniques are sufficiently mature to cope with the nonlinear diffusion equation, which can be accelerated by the MG scheme. Experimental results with both simulated data sets and real sets are provided, and the new method is demonstrated to achieve almost twice the speed of the state-of-the-art. Compared with previous efforts for finding a generalized representation to link bilateral filtering and nonlinear diffusion by adaptive filtering, a novel relationship between nonlinear diffusion and bilateral filtering is explored in this study by focusing attention on numerical calculus.