Text line and word segmentation of handwritten documents

In this paper, we present a segmentation methodology of handwritten documents in their distinct entities, namely, text lines and words. Text line segmentation is achieved by applying Hough transform on a subset of the document image connected components. A post-processing step includes the correction of possible false alarms, the detection of text lines that Hough transform failed to create and finally the efficient separation of vertically connected characters using a novel method based on skeletonization. Word segmentation is addressed as a two class problem. The distances between adjacent overlapped components in a text line are calculated using the combination of two distance metrics and each of them is categorized either as an inter- or an intra-word distance in a Gaussian mixture modeling framework. The performance of the proposed methodology is based on a consistent and concrete evaluation methodology that uses suitable performance measures in order to compare the text line segmentation and word segmentation results against the corresponding ground truth annotation. The efficiency of the proposed methodology is demonstrated by experimentation conducted on two different datasets: (a) on the test set of the ICDAR2007 handwriting segmentation competition and (b) on a set of historical handwritten documents.     

Synthetic handwritten CAPTCHAs

CAPTCHAs (completely automated public Turing test to tell computers and humans apart) are in common use today as a method for performing automated human verification online. The most popular type of CAPTCHA is the text recognition variety. However, many of the existing printed text CAPTCHAs have been broken by web-bots and are hence vulnerable to attack. We present an approach to use human-like handwriting for designing CAPTCHAs. A synthetic handwriting generation method is presented, where the generated textlines need to be as close as possible to human handwriting without being writer-specific. Such handwritten CAPTCHAs exploit the differential in handwriting reading proficiency between humans and machines. Test results show that when the generated textlines are further obfuscated with a set of deformations, machine recognition rates decrease considerably, compared to prior work, while human recognition rates remain the same.     

A routing-table-based adaptive and minimal routing scheme on network-on-chip architectures

In this paper, we present a routing algorithm that combines the shortest path routing and adaptive routing schemes for NoCs. In specific, routing follows the shortest path to ensure low latency and low energy consumption. This routing scheme requires routing information be stored in a series of routing tables created at the routers along the routing path from the source to the destination. To reduce the exploration space and timing cost for selecting the routing path, a routing list and routing table for each node are created off-line. Routing table is updated on-line to reflect the dynamic change of the network status to avoid network congestion. To alleviate the high hardware implementation cost associated with the routing tables, a method to help reduce the size of the routing tables is also introduced. Compared to the existing routing algorithms, the experimental results have confirmed that the proposed algorithm has better performance in terms of routing latency and power consumption.     

Embedding a fault-free hamiltonian cycle in a class of faulty generalized honeycomb tori

Generalized honeycomb torus (GHT) is recognized as an attractive alternative to existing torus interconnection networks in parallel computing systems. Assume that m and d are integers with m ? 2 and d ? 8. This paper addresses the fault-tolerant hamiltonicity of GHT(m, 2d, d) with fault set F = {(w, y), (x, y)}, where w < x, w + y is even and x + y is odd. We show that such a faulty GHT is hamiltonian by presenting a systematic method for constructing a fault-free hamiltonian cycle. This result reveals another appealing feature of GHTs.     

Efficient hardware architecture of 2D-scan-based wavelet watermarking for image and video

This paper describes an efficient hardware architecture of 2D-Scan-based-Wavelet watermarking for image and video. The potential application for this architecture includes broadcast monitoring of video sequences for High Definition Television (HDTV) and DVD protection and access control. The proposed 2D design allows even distribution of the processing load onto a set of filters, with each set performing the calculation for one dimension according to the scan-based process. The video protection is achieved by the insertion of watermarks bank within the middle frequency of wavelet coefficients related to video frames by their selective quantization. The 2-D DWT is applied for both video stream and watermark in order to make the watermarking scheme robust and perceptually invisible. The proposed architecture has a very simple control part, since the data are operated in a row-column-slice fashion. This organization reduces the requirement of on-chip memory. In addition, the control unit selects which coefficient to pass to the low-pass and high-pass filters. The on-chip memory will be small as compared to the input size since it depends solely on the filter sizes. Due to the pipelining, all filters are utilized for 100% of the time except during the start-up and wind-down times. The major contribution of this research is towards the selection of appropriate real time watermarking scheme and performing a trade-off between the algorithmic aspects of our proposed watermarking scheme and the hardware implementation technique. The hardware architecture is designed, as a watermarking based IP core with the Avalon interface related to NIOS embedded processor, and tested in order to evaluate the performance of our proposed watermarking algorithm. This architecture has been implemented on the Altera Stratix-II Field Programmable Gate Array (FPGA) prototyping board. Experimental results are presented to demonstrate the capability of the proposed watermarking system for real time applications and its robustness against malicious attacks.     

On event design in event-triggered feedback systems

This paper studies event design in event-triggered feedback systems. A novel event-triggering scheme is presented to ensure exponential stability of the resulting sampled-data system. The scheme postpones the triggering of events over previously proposed methods and therefore enlarges the intersampling period. The resulting intersampling periods and deadlines are bounded strictly away from zero when the continuous time system is input-to-state stable with respect to measurement errors.     

Maximal controllability of input constrained unstable systems by the addition of implicit constraints

The null controllable set of a system is the largest set of states that can be controlled to the origin. Control systems that have a region of attraction equal to the null controllable set are said to be maximally controllable closed-loop systems. In the case of open-loop unstable plants with amplitude constrained control it is well known that the null controllable set does not cover the entire state-space. Further the combination of input constraints and unstable system dynamics results in a set of state constraints which we call implicit constraints. It is shown that the simple inclusion of implicit constraints in a controller formulation results in a controller that achieves maximal controllability for a class of open-loop unstable systems.     

On the performance of high-gain observers with gain adaptation under measurement noise

We address the problem of state observation for a system whose dynamics may involve poorly known, perhaps even nonlocally Lipschitz functions and whose output measurement may be corrupted by noise. It is known that one way to cope with all these uncertainties and noise is to use a high-gain observer with a gain adapted on-line. The proposed method, while presented for a particular case, relies on a “generic” analysis tool based on the study of differential inequalities involving quadratic functions of the error system in two coordinate frames plus the gain adaptation law. We establish that, for bounded system solutions, the estimated state and the gain are bounded. Moreover, we provide an upper bound for the mean value of the error signals as a function of the observer parameters. Since due to perturbations the gain adaptation law may drive the observer/plant interconnection to nearby boundary of its stability region, oscillatory behavior may emerge. To overcome this issue, we suggest an adaptive procedure based on a space averaging technique involving several copies of the observer.     

Lossless convexification of a class of optimal control problems with non-convex control constraints

We consider a class of finite time horizon optimal control problems for continuous time linear systems with a convex cost, convex state constraints and non-convex control constraints. We propose a convex relaxation of the non-convex control constraints, and prove that the optimal solution of the relaxed problem is also an optimal solution for the original problem, which is referred to as the lossless convexification of the optimal control problem. The lossless convexification enables the use of interior point methods of convex optimization to obtain globally optimal solutions of the original non-convex optimal control problem. The solution approach is demonstrated on a number of planetary soft landing optimal control problems.