Developing embedded parallel image processing applications is usually a very hardware-dependent process, often using the single instruction multiple data (SIMD) paradigm, and requiring deep knowledge of the processors used. Furthermore, the application is tailored to a specific hardware platform, and if the chosen hardware does not meet the requirements, it must be rewritten for a new platform. We have proposed the use of design space exploration [9] to find the most suitable hardware platform for a certain application. This requires a hardware-independent program, and we use algorithmic skeletons [5] to achieve this, while exploiting the data parallelism inherent to low-level image processing. However, since different operations run best on different kinds of processors, we need to exploit task parallelism as well. This paper describes how we exploit task parallelism using an asynchronous remote procedure call (RPC) system, optimized for low-memory and sparsely connected systems such as smart cameras. It uses a futures [16]-like model to present a normal imperative C-interface to the user in which the skeleton calls are implicitly parallelized and pipelined. Simulation provides the task dependency graph and performance numbers for the mapping, which can be done at run time to facilitate data dependent branching. The result is an easy to program, platform independent framework which shields the user from the parallel implementation and mapping of his application, while efficiently utilizing on-chip memory and interconnect bandwidth.

This paper presents a 3D feature-based binocular tracking algorithm for tracking crowded people indoors. The algorithm consists of a two stage 3D feature points grouping method and a robust 3D feature-based tracking method. The two stage 3D feature points grouping method can use kernel-based ISODATA method to detect people accurately even though the part or almost full occlusion occurs among people in surveillance area. The robust 3D feature-based Tracking method combines interacting multiple model (IMM) method with a cascade multiple feature data association method. The robust 3D feature-based tracking method not only manages the generation and disappearance of a trajectory, but also can deal with the interaction of people and track people maneuvering. Experimental results demonstrate the robustness and efficiency of the proposed framework. It is real-time and not sensitive to the variable frame to frame interval time. It also can deal with the occlusion of people and do well in those cases that people rotate and wriggle.

We achieved first dynamic all-optical signal processing with a bandgap-engineered MZI SOA all-optical switch. The wide-gap Selective Area Growth (SAG) technique was used to provide multi-bandgap materials with a single step epitaxy. The maximum photoluminescence (PL) peak shift obtained between the active region and the passive region was 192 nm. The static current switching with the fabricated switch indicated a large carrier induced refractive index change; up to 14 π phase shift was obtained with 60 mA injection in the SOA. The carrier recovery time of the SOA for obtaining a phase shift of π was estimated to be 250-300 ps. A clear eye pattern was obtained in 2.5 Gbps all-optical wavelength conversion. This is the first all-optical wavelength conversion demonstration with a bandgap-engineered PIC with either selective area growth or quantum-well intermixing techniques.

We propose a novel strategy to obtain a high spatio-temporal resolution video. To this end, we introduce a dual sensor camera that can capture two video sequences with the same field of view simultaneously. These sequences record high resolution with low frame rate and low resolution with high frame rate. This paper presents an algorithm to synthesize a high spatio-temporal resolution video from these two video sequences by using motion compensation and spectral fusion. We confirm that the proposed method improves the resolution and frame rate of the synthesized video.

Intercarrier interference will cause the loss of subchannel orthogonality and increase the error floor in proportion to the Doppler frequency. In this paper, we firstly analyze the generation mechanism of intercarrier interference in OFDM. Then we propose an O(N log2N) complexity ICI equalizer for OFDM systems in the presence of double selective fading which is mainly bases on FFT operation. Simulation result shows that with only 6 iterations LCD-FFT can achieve better performance than the LS-equalizer. After 10 iterations LCD-FFT performs almost the same as MMSE equalizer.

A new method for automatically building statistical shape models from a set of training examples and in particular from a class of hands. In this study, we utilise a novel approach to automatically recover the shape of hand outlines from a series of 2D training images. Automated landmark extraction is accomplished through the use of the self-organising model the growing neural gas (GNG) network, which is able to learn and preserve the topological relations of a given set of input patterns without requiring a priori knowledge of the structure of the input space. The GNG is compared to other self-organising networks such as Kohonen and Neural Gas (NG) maps and results are given for the training set of hand outlines, showing that the proposed method preserves accurate models.

We present room temperature current voltage characteristics from SiGe interband tunneling diodes epitaxially grown on highly resistive Si(001) substrates. In this case, a maximum peak to valley current ratio (PVCR) of 5.65 was obtained. The possible integration of a SiGe tunnel diode with a strained Si transistor lead us to investigate the growth of SiGe interband tunneling diodes on Si0.7Ge0.3 virtual substrates. A careful optimization of the layer structure leads to a maximum PVCR of 1.36 at room temperature. The latter value can be further increased to 2.26 at 3.7 K. Our results demonstrate that high quality SiGe interband tunneling diodes can be realized, which is of great interest for future memory and high speed applications.

This paper discusses a cyclic prefixed single carrier frequency-domain equalization (SC-FDE) scheme with two types of transmit diversity. Firstly, we propose a SC-FDE system with space-frequency block coding (SFBC). The transmit sequence of the proposed system is designed to have spatial and frequency diversities, which is equivalent to the SFBC. The corresponding combining receiver is derived under a minimum mean square error (MMSE) criterion. It is shown that the proposed system significantly outperforms the SC-FDE system with space-time block coding (STBC) over fast fading channels, while providing lower computational complexity than orthogonal frequency division multiplexing (OFDM) combined with SFBC. We verify the performance of two-branch transmit diversity systems including the proposed one through bit error rate (BER) analysis. Secondly, as a scheme that combines STBC and SFBC, a space-time-frequency block code (STFBC) SC-FDE system is presented. Computer simulation results show that the proposed STFBC SC-FDE system has better immunity to the distortion caused by both fast fading and severe frequency selective fading, compared to the SC-FDE system with the STBC or the SFBC scheme. Complexity analysis is also conducted to compare their computational loads of the transceiver. It is shown that the proposed STFBC SC-FDE system has lower computational complexity than the STFBC OFDM system.

This paper proposes a novel image processing method based on a percolation model. The percolation model is used to represent the natural phenomenon of the permeation of liquid. The percolation takes into account the connectivity among the neighborhoods. In the proposed method, a cluster formation by the percolation process is performed first. Then, feature extraction from the cluster is carried out. Therefore, this method is a type of scalable window processing for realizing a robust and flexible feature extraction. The effectiveness of proposed method was verified by experiments on crack detection, noise reduction, and edge detection.

In this paper, we study how a multidimensional local binary pattern (LBP) texture feature data can be visually explored and analyzed. The goal is to determine how true paper properties can be characterized with local texture features from visible light images. We utilize isometric feature mapping (Isomap) for the LBP texture feature data and perform non-linear dimensionality reduction for the data. These 2D projections are then visualized with original images to study data properties. Visualization is utilized in the manner of selecting texture models for unlabeled data and analyzing feature performance when building a training set for a classifier. The approach is experimented on with simulated image data illustrating different paper properties and on-line transilluminated paper images taken from a running paper web in the paper mill. The simulated image set is used to acquire quantitative figures on the performance while the analysis of real-world data is an example of semi-supervised learning.

Multiple-input multiple-output (MIMO) multiplexing has recently been attracting considerable attention for increasing the transmission rate in a limited bandwidth. In MIMO multiplexing, the signals transmitted simultaneously from different transmit antennas must be separated and detected at a receiver. Maximum likelihood detection with QR-decomposition and M-algorithm (QRM-MLD) can achieve good performance while keeping computational complexity low. However, when the number of surviving symbol replica candidates in the M-algorithm is set to be small, the performance of QRM-MLD degrades compared to that of MLD because of wrong selection of surviving symbol replica candidates. Furthermore, when channel estimation is inaccurate, accurate signal ranking and QR-decomposition cannot be carried out. In this paper, we propose an iterative QRM-MLD with decision directed channel estimation to improve the packet error rate (PER) performance. In the proposed QRM-MLD, decision feedback data symbols are also used for channel estimation in addition to pilot symbols in order to improve the channel estimation accuracy. Signal detection/channel estimation are then carried out in an iterative fashion. Computer simulation results show that the proposed QRM-MLD reduces the required average received Eb/N0 for PER of 10-2 by about 1.2 dB compared to the conventional method using orthogonal pilot symbols only.

We present a method for classifying image pixels of real images into multiple photometric factors: specular reflection, diffuse reflection, attached shadows and cast shadows. Conventional photometric linearization methods cannot correctly classify pixels under near point light sources, since they assume parallel light. To satisfy this assumption, our method utilizes a photometric linearization method that divides images into small regions. It also propagates linearization coefficients from neighboring regions. Our experimental results show that the proposed method can correctly classify image pixels into photometric factors, even if images are obtained under near point light sources.

The most powerful channel coding schemes, namely those based on turbo codes and low-density parity-check (LDPC) Gallager codes, have in common the principle of iterative decoding. However, the relative coding structures and decoding algorithms are substantially different. This paper presents a 2048-bit, rate-1/2 soft decision decoder for a new class of codes known as Turbo Gallager Codes. These codes are turbo codes with properly chosen component convolutional codes such that they can be successfully decoded by means of the decoding algorithm used for LDPC codes, i.e., the belief propagation algorithm working on the code Tanner graph. These coding schemes are important in practical terms for two reasons: (i) they can be encoded as classical turbo codes, giving a solution to the encoding problem of LDPC codes; (ii) they can also be decoded in a fully parallel manner, partially overcoming the routing congestion bottleneck of parallel decoder VLSI implementations thanks to the locality of the interconnections. The implemented decoder can support up to 1 Gbit/s data rate and performs up to 48 decoding iterations ensuring both high throughput and good coding gain. In order to evaluate the performance and the gate complexity of the decoder VLSI architecture, it has been synthesized in a 0.18 µm standard-cell CMOS technology.

The minimization problem of an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints is formulated for a class of two-dimensional (2-D) state-space digital filters. First, the problem is converted into an unconstrained optimization problem by using linear-algebraic techniques. Next, the unconstrained optimization problem is solved by applying an efficient quasi-Newton algorithm with closed-form formula for gradient evaluation. The coordinate transformation matrix obtained is then used to synthesize the optimal 2-D state-space filter structure that minimizes the L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints. Finally, a numerical example is presented to illustrate the utility of the proposed technique.

The EDD connection admission control scheme has been proposed for supporting real-time communication in packet-switched networks. In the scheme, when a connection establishment request occurs, the worst-case link delay in each link along the connection is calculated to determine whether the request can be accepted or not. In order to calculate the worst-case link delay, we must perform a check called the point schedulability check for each of some discrete time instants (checkpoints). Therefore when there are many checkpoints, the worst-case link delay calculation is time-consuming. We have proposed a high-speed calculation method. The method finds some checkpoints for which the point schedulability check need not be performed and removes such unnecessary checkpoints in advance before a connection establishment request occurs, and the check is performed for each of the remaining checkpoints after the request occurs. However, the method is not so effective under the situation that the maximum packet length in networks is large, because the method can find few unnecessary checkpoints under the situation. This paper proposes a new high-speed calculation method. We relax the condition which determines whether or not the point schedulability check need not be performed for each checkpoint in our previous method and derive a new condition for finding unnecessary checkpoints. Using the proposed method based on the new condition, we can increase the number of unnecessary checkpoints compared to our previous method. Numerical examples which are obtained by extensive simulation show that the proposed method can attain as much as about 50 times speedup.

In this paper, a new family S(r) of 2n binary sequences of period 2n-1 is proposed, where n ≡ 2 mod 4 and gcd(r, 2n/2-1)=1. The presented family takes 4-valued out-of-phase auto- and cross-correlation values -1, 2n/2-1, and 2n/2+1-1, and its correlation distribution is determined. For r=2(n-2)/4-1, each sequence in S(r), except the unique ideal autocorrelation sequence in the family, is proved to have a large linear span n2n/2-2, whilst the linear span of the latter is n2(n-2)/4-1.

The noise robustness of an audio fingerprinting system is one of the most important issues in music information retrieval by the content-based audio identification technique. In a real environment, sound recordings are commonly distorted by channel and background noise. Recently, Philips published a robust and efficient audio fingerprinting system for audio identification. To extract a robust and efficient audio fingerprint, Philips applied the first derivative (differential) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the noise robustness of Philips' audio fingerprinting scheme is still insufficient. In this paper, we introduce an extension method of the audio fingerprinting scheme for the enhancement of noise robustness. As an alternative to frequency filtering, a type of band-pass filter, instead of a high-pass filter, is used to achieve robustness to background noise in a real situation. Our experimental results show that the proposed filter improves the noise robustness in audio identification.

A multi-stage approach -- which is fast, robust and easy to train -- for a face-detection system is proposed. Motivated by the work of Viola and Jones [1], this approach uses a cascade of classifiers to yield a coarse-to-fine strategy to reduce significantly detection time while maintaining a high detection rate. However, it is distinguished from previous work by two features. First, a new stage has been added to detect face candidate regions more quickly by using a larger window size and larger moving step size. Second, support vector machine (SVM) classifiers are used instead of AdaBoost classifiers in the last stage, and Haar wavelet features selected by the previous stage are reused for the SVM classifiers robustly and efficiently. By combining AdaBoost and SVM classifiers, the final system can achieve both fast and robust detection because most non-face patterns are rejected quickly in earlier layers, while only a small number of promising face patterns are classified robustly in later layers. The proposed multi-stage-based system has been shown to run faster than the original AdaBoost-based system while maintaining comparable accuracy.

One of the key technologies to realize future broadband mobile communications is orthogonal frequency division multiplexing (OFDM) transmission. However, the peak-to-average power ratio (PAPR) in OFDM transmission is so much larger than that in single carrier transmission that its adoption in mobile communication systems is uncertain. This paper evaluates the transmission performance possible with iterative peak reduction to design more efficient OFDM transmitters. The PAPR reduction effect and bit error rate (BER) performance are clarified by computer simulations. We calculate the set PAPR value that achieves a target PAPR in the iterative peak reduction method. The required Eb/N0 performance is evaluated under the calculated PAPR condition. The results are effective in designing the back-off value of a transmission power amplifier given fixed transmission quality and computational complexity.

In this study, we propose an adaptive handoff scheme with dynamic hysteresis value for cellular communications, which is based on distance between the mobile station and the serving base station. Performance is evaluated in terms of the expected number of handoffs, the expected handoff delay, standard deviation of handoff location, and the expected link degradation probability as well. Numerical results and simulations show that the proposed scheme outperforms the handoff schemes with static hysteresis levels. The effect of distance error is also discussed.