The Euler number of a binary image is an important topological property for pattern recognition, image analysis, and computer vision. A famous method for computing the Euler number of a binary image is by counting certain patterns of bit-quads in the image, which has been improved by scanning three rows once to process two bit-quads simultaneously. This paper studies the bit-quad-based Euler number computing problem. We show that for a bit-quad-based Euler number computing algorithm, with the increase of the number of bit-quads being processed simultaneously, on the one hand, the average number of pixels to be checked for processing a bit-quad will decrease in theory, and on the other hand, the length of the codes for implementing the algorithm will increase, which will make the algorithm less efficient in practice. Experimental results on various types of images demonstrated that scanning five rows once and processing four bit-quads simultaneously is the optimal tradeoff, and that the optimal bit-quad-based Euler number computing algorithm is more efficient than other Euler number computing algorithms.

Research efforts initiated by the EXAT Initiative are described to realize Exabit/s optical communications, utilizing the 3M technologies, i.e. multi-core fiber, multi-mode control and multi-level modulation.

In OFDM systems, link performance depends heavily on the estimation of symbol-timing and frequency offsets. Performance sensitivity to these estimates is a major drawback of OFDM systems. Timing errors destroy the orthogonality of OFDM signals and lead to inter-symbol interference (ISI) and inter-carrier interference (ICI). The interference due to timing errors can be exploited as a metric for symbol-timing synchronization. In this paper, we propose a novel method to extract interference components using a DFT of the upsampled OFDM signals. Mathematical analysis and formulation are given for the dependence of interference on timing errors. From a numerical analysis, the proposed interference estimation shows robustness against channel dispersion.

To drastically increase the splitting ratio of extended-reach (40km span) time- and wavelength-division multiplexed passive optical networks (WDM/TDM-PONs), we modify the gain control scheme of our automatic gain controlled semiconductor optical amplifiers (AGC-SOAs) that were developed to support upstream transmission in long-reach systems. While the original AGC-SOAs are located outside the central office (CO) as repeaters, the new AGC-SOAs are located inside the CO and connected to each branch of an optical splitter in the CO. This arrangement has the potential to greatly reduce the costs of CO-sited equipment as they are shared by many more users if the new gain control scheme works properly even when the input optical powers are low. We develop a prototype and experimentally confirm its effectiveness in increasing the splitting ratio of extended-reach systems to 512.

Object detection is at the heart of nearly all the computer vision systems. Standard off-the-shelf embedded processors are hard to meet the trade-offs among performance, power consumption and flexibility required by object detection applications. Therefore, this paper presents an Application Specific Instruction set Processor (ASIP) for object detection using AdaBoost-based learning algorithm with Haar-like features as weak classifiers. Algorithm optimizations are employed to reduce memory bandwidth requirements without losing reliability. In the proposed ASIP, Single Instruction Multiple Data (SIMD) architecture is adopted for fully exploiting data-level parallelism inherent to the target algorithm. With adding pipeline stages, application-specific hardware components and custom instructions, the AdaBoost algorithm is accelerated by a factor of 13.7x compared to the optimized pure software implementation. Compared with ARM946 and TMS320C64+, our ASIP shows 32x and 7x better throughput, 10x and 224x better area efficiency, 6.8x and 18.8x better power efficiency, respectively. Furthermore, compared to hard-wired designs, evaluation results show an advantage of the proposed architecture in terms of chip area efficiency while maintain a reliable performance and achieve real-time object detection at 32fps on VGA video.

This letter proposes a class of polyphase zero correlation zone (ZCZ) sequence sets with low inter-set cross-correlation property. The proposed ZCZ sequence sets are constructed from DFT matrices and r-coincidence sequences. Each ZCZ sequence set is optimal, and the absolute value of the cross-correlation function of sequences from different sets is less than or equal to $rsqrt{N}$, where N denotes the length of each sequence. These ZCZ sequence sets are suitable for multiuser environments.

High Efficiency Video Coding is a new video coding standard after H.264/AVC. By introducing a flexible coding unit, which can be recursively divided from 64×64 to 8×8 blocks in a Quadtree-Structure, HEVC achieves significantly higher coding efficiency than the previous standards. With the flexible CU structure, HEVC can effectively adapt to highly varying contents with a smaller CU or to flat contents with a larger CU, making it suitable for applications from mobile video to super high definition television. On the other hand, CU division does incur high computational cost for HEVC. In this paper, we propose a simple and fast CU division algorithm by using only a subset of pixels to determine when CU division happens. Experiment results show that our algorithm can achieve prediction quality close to HEVC Test Model with much lower computational cost.

Improvement of conventional networks with an incremental approach is an important design method for the development of the future internet. For this approach, we are developing a future aggregation network based on passive optical network (PON) technology to achieve both cost-effectiveness and high reliability. In this paper, we propose a timeslot (TS) synchronization method for sharing a TS from an optical burst mode transceiver between any route of arbitrary fiber length by changing both the route of the TS transmission and the TS control timing on the optical burst mode transceiver. We show the effectiveness of the proposed method for exchanging TSs in bidirectional bufferless wavelength division multiplexing (WDM) and time division multiplexing (TDM) multi-ring networks under the condition of the occurrence of a link failure through prototype systems. Also, we evaluate the reduction of the required number of optical interfaces in a multi-ring network by applying the proposed method.

This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.

This paper proposes a dynamic spectrum controlled (DSTC) channel allocation algorithm to increase the total throughput of satellite communication (SATCOM) systems. To effectively use satellite resources such as the satellite's maximum transponder bandwidth and maximum transmission power and to handle the propagation gain variation at all earth stations, the DSTC algorithm uses two new transmission techniques: spectrum compression and spectrum division. The algorithm controls various transmission parameters, such as the spectrum compression ratio, number of spectrum divisions, combination of modulation method and FEC coding rate (MODCOD), transmission power, and spectrum bandwidth to ensure a constant transmission bit rate under variable propagation conditions. Simulation results show that the DSTC algorithm achieves up to 1.6 times higher throughput than a simple MODCOD-based algorithm.

The proliferation of diverse kinds of programming languages and platforms makes it a common need to have the same functionality implemented in different languages for different platforms, such as Java for Android applications and C# for Windows phone applications. Although versions of code written in different languages appear syntactically quite different from each other, they are intended to implement the same software and typically contain many code snippets that implement similar functionalities, which we call cross-language clones. When the version of code in one language evolves according to changing functionality requirements and/or bug fixes, its cross-language clones may also need be changed to maintain consistent implementations for the same functionality. Thus, it is needed to have automated ways to locate and track cross-language clones within the evolving software. In the literature, approaches for detecting cross-language clones are only for languages that share a common intermediate language (such as the .NET language family) because they are built on techniques for detecting single-language clones. To extend the capability of cross-language clone detection to more diverse kinds of languages, we propose a novel automated approach, CLCMiner, without the need of an intermediate language. It mines such clones from revision histories, based on our assumption that revisions to different versions of code implemented in different languages may naturally reflect how programmers change cross-language clones in practice, and that similarities among the revisions (referred to as clones in diffs or diff clones) may indicate actual similar code. We have implemented a prototype and applied it to ten open source projects implementations in both Java and C#. The reported clones that occur in revision histories are of high precisions (89% on average) and recalls (95% on average). Compared with token-based code clone detection tools that can treat code as plain texts, our tool can detect significantly more cross-language clones. All the evaluation results demonstrate the feasibility of revision-history based techniques for detecting cross-language clones without intermediates and point to promising future work.

Advances in intelligent vehicle systems have led to modern automobiles being able to aid drivers with tasks such as lane following and automatic braking. Such automated driving tasks increasingly require reliable ego-localization. Although there is a large number of sensors that can be employed for this purpose, the use of a single camera still remains one of the most appealing, but also one of the most challenging. GPS localization in urban environments may not be reliable enough for automated driving systems, and various combinations of range sensors and inertial navigation systems are often too complex and expensive for a consumer setup. Therefore accurate localization with a single camera is a desirable goal. In this paper we propose a method for vehicle localization using images captured from a single vehicle-mounted camera and a pre-constructed database. Image feature points are extracted, but the calculation of camera poses is not required — instead we make use of the feature points' scale. For image feature-based localization methods, matching of many features against candidate database images is time consuming, and database sizes can become large. Therefore, here we propose a method that constructs a database with pre-matched features of known good scale stability. This limits the number of unused and incorrectly matched features, and allows recording of the database scales into “tracklets”. These “Feature scale tracklets” are used for fast image match voting based on scale comparison with corresponding query image features. This process reduces the number of image-to-image matching iterations that need to be performed while improving the localization stability. We also present an analysis of the system performance using a dataset with high accuracy ground truth. We demonstrate robust vehicle positioning even in challenging lane change and real traffic situations.

Inter-person occlusion handling is a critical issue in the field of tracking, and it has been extensively researched. Several state-of-the-art methods have been proposed, such as focusing on the appearance of the targets or utilizing knowledge of the scene. In contrast with the approaches proposed in the literature, we propose to address this issue using a social interaction model, which allows us to explore spatio-temporal information pertaining to the targets involved in the occlusion situation. Our experimental results show promising results compared with those obtained using other methods.

In this paper, we present the channel estimation (CE) problem in the orthogonal frequency division multiplexing system with offset quadrature amplitude modulation (OFDM/OQAM). Most CE methods rely on the assumption of a low frequency selective channel to tackle the problem in a way similar to OFDM. However, these methods would result in a severe performance degradation of the channel estimation when the assumption is not quite inaccurate. Instead, we focus on estimating the channel impulse response (CIR) itself which makes no assumption on the degree of frequency selectivity of the channels. After describing the main idea of this technique, we present an iterative CE method that does not require zero-value guard symbols in the preamble and consequently improves the spectral efficiency. This is done by the iterative estimation of the unknown transmitted data adjacent to the preamble. Analysis and simulation results validate the efficacy of the proposed method in multipath fading channels.

This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.

Controlling the peak-to-mean envelope power ratio (PMEPR) of orthogonal frequency-division multiplexed (OFDM) transmissions is a significant obstacle in many low-cost applications of OFDM. An coding approach proposed by H.R. Sadjadpour presents non-square M-QAM symbols as a combination of QPSK and BPSK signals when M=22n+1, and then uses QPSK and BPSK Golay (or Golay-like) sequences with a constant PMEPR to generate M-QAM sequences. This paper proposes a new scheme in which M-QAM sequences are generated by QPSK and BPSK sequences with variable PMEPRs. In other words, this new scheme is a general case of the existing approach. As a result, the code rate of the new sequence is significantly improved, while the upper bound of its PMEPR remains at a comparative level.

Based on a perfect Gaussian integer sequence, shift and combination operations are performed to construct Gaussian integer sequences with zero correlation zone (ZCZ). The resultant sequence sets are optimal or almost optimal with respect to the Tang-Fan-Matsufuji bound. Furthermore, the ZCZ Gaussian integer sequence sets can be provided for quasi-synchronous code-division multiple-access systems to increase transmission data rate and reduce interference.

This paper newly proposes and theoretically analyzes the performance of multi-hop free-space optical (FSO) systems employing optical amplify-and-forward (OAF) relaying technique and wavelength division multiplexing (WDM). The proposed system can provide a low cost, low latency, high flexibility, and large bandwidth access network for multiple users in areas where installation of optical fiber is unfavorable. In WDM/FSO systems, WDM channels suffer from the interchannel crosstalk while FSO channels can be severely affected by the atmospheric turbulence. These impairments together with the accumulation of background and amplifying noises over multiple relays significantly degrade the overall system performance. To deal with this problem, the use of the M-ary pulse position modulation (M-PPM) together with the OAF relaying technique is advocated as a powerful remedy to mitigate the effects of atmospheric turbulence. For the performance analysis, we use a realistic model of Gaussian pulse propagation to investigate major atmospheric effects, including signal turbulence and pulse broadening. We qualitatively discuss the impact of various system parameters, including the required average transmitted powers per information bit corresponding to specific values of bit error rate (BER), transmission distance, number of relays, and turbulence strength. Our numerical results are also thoroughly validated by Monte-Carlo (M-C) simulations.

A method for increasing alignment tolerance in simple multiple-stream transmission is described. Its use of π-shifted antenna directivity phase enables it to cancel interference even when antenna placement deviations occur. The interference cancellation by using π-shifted directivities provides higher alignment tolerance than that with conventional fixed weight methods. It also provides smaller channel gain variation than can be obtained using fixed weights even when antenna displacement occurs. An objective function is described that is determined by the alignment tolerance. The function is defined to maximize the alignment tolerance. The method's validity is confirmed by an experimental analysis of two-stream transmission in which the alignment tolerance of the proposed method is compared to that of conventional fixed weight methods.

Many selected mapping (SLM) schemes have been proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal sequences. In this paper, an efficient selection (ES) method of the OFDM signal sequence with minimum PAPR among many alternative OFDM signal sequences is proposed; it supports various SLM schemes. Utilizing the fact that OFDM signal components can be sequentially generated in many SLM schemes, the generation and PAPR observation of the OFDM signal sequence are processed concurrently. While the u-th alternative OFDM signal components are being generated, by applying the proposed ES method, the generation of that alternative OFDM signal components can be interrupted (or stopped) according to the selection criteria of the best OFDM signal sequence in the considered SLM scheme. Such interruption substantially reduces the average computational complexity of SLM schemes without degradation of PAPR reduction performance, which is confirmed by analytical and numerical results. Note that the proposed method is not an isolated SLM scheme but a subsidiary method which can be easily adopted in many SLM schemes in order to further reduce the computational complexity of considered SLM schemes.