Benchmarking recognition results on camera captured word image data sets

We have benchmarked the maximum obtainable recognition accuracy on five publicly available standard word image data sets using semi-automated segmentation and a commercial OCR. These images have been cropped from camera captured scene images, born digital images (BDI) and street view images. Using the Matlab based tool developed by us, we have annotated at the pixel level more than 3600 word images from the five data sets. The word images binarized by the tool, as well as by our own midline analysis and propagation of segmentation (MAPS) algorithm are recognized using the trial version of Nuance Omnipage OCR and these two results are compared with the best reported in the literature. The benchmark word recognition rates obtained on ICDAR 2003, Sign evaluation, Street view, Born-digital and ICDAR 2011 data sets are 83.9%, 89.3%, 79.6%, 88.5% and 86.7%, respectively. The results obtained from MAPS binarized word images without the use of any lexicon are 64.5% and 71.7% for ICDAR 2003 and 2011 respectively, and these values are higher than the best reported values in the literature of 61.1% and 41.2%, respectively. MAPS results of 82.8% for BDI 2011 dataset matches the performance of the state of the art method based on power law transform.

Ages and relative sizes of pre-2004 tsunamis in the Bay of Bengal inferred from geologic evidence in the Andaman and Nicobar Islands

Geologic evidence along the northern part of the 2004 Aceh-Andaman rupture suggests that this region generated as many as five tsunamis in the prior 2000years. We identify this evidence by drawing analogy with geologic records of land-level change and the tsunami in 2004 from the Andaman and Nicobar Islands (A&N). These analogs include subsided mangrove swamps, uplifted coral terraces, liquefaction, and organic soils coated by sand and coral rubble. The pre-2004 evidence varies in potency, and materials dated provide limiting ages on inferred tsunamis. The earliest tsunamis occurred between the second and sixth centuries A.D., evidenced by coral debris of the southern Car Nicobar Island. A subsequent tsunami, probably in the range A.D. 770-1040, is inferred from deposits both in A&N and on the Indian subcontinent. It is the strongest candidate for a 2004-caliber earthquake in the past 2000years. A&N also contain tsunami deposits from A.D. 1250 to 1450 that probably match those previously reported from Sumatra and Thailand, and which likely date to the 1390s or 1450s if correlated with well-dated coral uplift offshore Sumatra. Thus, age data from A&N suggest that within the uncertainties in estimating relative sizes of paleo-earthquakes and tsunamis, the 1000year interval can be divided in half by the earthquake or earthquakes of A.D. 1250-1450 of magnitude >8.0 and consequent tsunamis. Unlike the transoceanic tsunamis generated by full or partial rupture of the subduction interface, the A&N geology further provides evidence for the smaller-sized historical tsunamis of 1762 and 1881, which may have been damaging locally.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Efficient gradient-free simplex method for estimation of optical properties in image-guided diffuse optical tomography

Typical image-guided diffuse optical tomographic image reconstruction procedures involve reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem less ill-posed compared to traditional underdetermined cases. Still, the methods that are deployed in this case are same as those used for traditional diffuse optical image reconstruction, which involves a regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method is proposed here to perform the image reconstruction procedure and is shown to provide solutions that closely match ones obtained using established methods, even in highly noisy data. The proposed method also has the distinct advantage of being more efficient owing to being regularization free, involving only repeated forward calculations. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

DSA image registration using non-uniform MRF model and pivotal control points

In order to reduce the motion artifacts in DSA, non-rigid image registration is commonly used before subtracting the mask from the contrast image. Since DSA registration requires a set of spatially non-uniform control points, a conventional MRF model is not very efficient. In this paper, we introduce the concept of pivotal and non-pivotal control points to address this, and propose a non-uniform MRF for DSA registration. We use quad-trees in a novel way to generate the non-uniform grid of control points. Our MRF formulation produces a smooth displacement field and therefore results in better artifact reduction than that of registering the control points independently. We achieve improved computational performance using pivotal control points without compromising on the artifact reduction. We have tested our approach using several clinical data sets, and have presented the results of quantitative analysis, clinical assessment and performance improvement on a GPU. (C) 2013 Elsevier Ltd. All rights reserved.

Taylor series expansion based multidimensional image reconstruction for confocal and 4pi microscopy

We propose and experimentally demonstrate a three-dimensional (3D) image reconstruction methodology based on Taylor series approximation (TSA) in a Bayesian image reconstruction formulation. TSA incorporates the requirement of analyticity in the image domain, and acts as a finite impulse response filter. This technique is validated on images obtained from widefield, confocal laser scanning fluorescence microscopy and two-photon excited 4pi (2PE-4pi) fluorescence microscopy. Studies on simulated 3D objects, mitochondria-tagged yeast cells (labeled with Mitotracker Orange) and mitochondrial networks (tagged with Green fluorescent protein) show a signal-to-background improvement of 40% and resolution enhancement from 360 to 240 nm. This technique can easily be extended to other imaging modalities (single plane illumination microscopy (SPIM), individual molecule localization SPIM, stimulated emission depletion microscopy and its variants).

Stall flutter of NACA 0012 airfoil at low Reynolds numbers

In the present work, we experimentally study and demarcate the stall flutter boundaries of a NACA 0012 airfoil at low Reynolds numbers (Re similar to 10(4)) by measuring the forces and flow fields around the airfoil when it is forced to oscillate. The airfoil is placed at large mean angle of attack (alpha(m)), and is forced to undergo small amplitude pitch oscillations, the amplitude (Delta alpha) and frequency (f) of which are systematically varied. The unsteady loads on the oscillating airfoil are directly measured, and are used to calculate the energy transfer to the airfoil from the flow. These measurements indicate that for large mean angles of attack of the airfoil (alpha(m)), there is positive energy transfer to the airfoil over a range of reduced frequencies (k=pi fc/U), indicating that there is a possibility of airfoil excitation or stall flutter even at these low Re (c=chord length). Outside this range of reduced frequencies, the energy transfer is negative and under these conditions the oscillations would be damped. Particle Image Velocimetry (PIV) measurements of the flow around the oscillating airfoil show that the shear layer separates from the leading edge and forms a leading edge vortex, although it is not very clear and distinct due to the low oscillation amplitudes. On the other hand, the shear layer formed after separation is found to clearly move periodically away from the airfoil suction surface and towards it with a phase lag to the airfoil oscillations. The phase of the shear layer motion with respect to the airfoil motions shows a clear difference between the exciting and the damping case.

Image reconstruction enables high resolution imaging at large penetration depths in fluorescence microscopy

Imaging thick specimen at a large penetration depth is a challenge in biophysics and material science. Refractive index mismatch results in spherical aberration that is responsible for streaking artifacts, while Poissonian nature of photon emission and scattering introduces noise in the acquired three-dimensional image. To overcome these unwanted artifacts, we introduced a two-fold approach: first, point-spread function modeling with correction for spherical aberration and second, employing maximum-likelihood reconstruction technique to eliminate noise. Experimental results on fluorescent nano-beads and fluorescently coated yeast cells (encaged in Agarose gel) shows substantial minimization of artifacts. The noise is substantially suppressed, whereas the side-lobes (generated by streaking effect) drops by 48.6% as compared to raw data at a depth of 150 mu m. Proposed imaging technique can be integrated to sophisticated fluorescence imaging techniques for rendering high resolution beyond 150 mu m mark. (C) 2013 AIP Publishing LLC.

Locating the attacker of wormhole attack by using the honeypot

Mobile Ad hoc Networks (MANETs) having strikingly superior features also come with notable disadvantage and troubles and the most exigent amongst all being security related issues. Such an ringent network dexterously pave approach for the malicious nodes. Hence providing security is a tedious task. For such a dynamic environment, a security system which dynamically observes the attacker's plans and protect the highly sophisticated resources is in high demand. In this paper we present a method of providing security against wormhole attacks to a MANET by learning about the environment dynamically and adapting itself to avoid malicious nodes. We accomplish this with the assistance of Honeypot. Our method predicts the wormhole attack that may take place and protect the resources well-in advance. Also it cleverly deal with the attacker by using previous history and different type of messages to locate the attacker. Several experiments suggest that the system is accurate in handling wormhole attack.

Experimental analysis of composite single-lap joints using digital image correlation and comparison with theoretical models

The demand for energy efficient, low weight structures has boosted the use of composite structures assembled using increased quantities of structural adhesives. Bonded structures may be subjected to severe working environments such as high temperature and moisture due to which the adhesive gets degraded over a period of time. This reduces the strength of a joint and leads to premature failure. Measurement of strains in the adhesive bondline at any point of time during service may be beneficial as an assessment can be made on the integrity of a joint and necessary preventive actions may be taken before failure. This paper presents an experimental approach of measuring peel and shear strains in the adhesive bondline of composite single-lap joints using digital image correlation. Different sets of composite adhesive joints with varied bond quality were prepared and subjected to tensile load during which digital images were taken and processed using digital image correlation software. The measured peel strain at the joint edge showed a rapid increase with the initiation of a crack till failure of the joint. The measured strains were used to compute the corresponding stresses assuming a plane strain condition and the results were compared with stresses predicted using theoretical models, namely linear and nonlinear adhesive beam models. A similar trend in stress distribution was observed. Further comparison of peel and shear strains also exhibited similar trend for both healthy and degraded joints. Maximum peel stress failure criterion was used to predict the failure load of a composite adhesive joint and a comparison was made between predicted and actual failure loads. The predicted failure loads from theoretical models were found to be higher than the actual failure load for all the joints.

An early in-situ stress signature of the AlN-Si pre-growth interface for successful integration of nitrides with (111) Si

The integration of Metal Organic Chemical Vapor Deposition (MOCVD) grown group III-A nitride device stacks on Si (111) substrates is critically dependent on the quality of the first AlN buffer layer grown. A Si surface that is both oxide-free and smooth is a primary requirement for nucleating such layers. A single parameter, the AlN layer growth stress, is shown to be an early (within 50 nm), clear (<0.5 GPa versus > 1GPa), and fail-safe indicator of the pre-growth surface, and the AlN quality required for successful epitaxy. Grain coalescence model for stress generation is used to correlate growth stress, the AlN-Si interface, and crystal quality. (C) 2013 AIP Publishing LLC.

Long ranged structural modulation in the pre-morphotropic phase boundary cubic-like state of the lead-free piezoelectric Na1/2Bi1/2TiO3-BaTiO3

The nature of the pre-morphotropic phase boundary (MPB) cubic-like state in the lead-free piezoelectric ceramics (1-x)Na1/2Bi1/2TiO3-(x)BaTiO3 at x similar to 0.06 has been examined in detail by electric field and temperature dependent neutron diffraction, x-ray diffraction, dielectric and ferroelectric characterization. The superlattice reflections in the neutron diffraction patterns cannot be explained with the tetragonal P4bm and the rhombohedral (R3c) phase coexistence model. The cubic like state is rather a result of long ranged modulated complex octahedral tilt. This modulated structure exhibits anomalously large dielectric dispersion. The modulated structure transforms to a MPB state on poling. The field-stabilized MPB state is destroyed and the modulated structure is restored on heating the poled specimen above the Vogel-Fulcher freezing temperature. The results show the predominant role of competing octahedral tilts in determining the nature of structural and polar states in Na1/2Bi1/2TiO3-based ferroelectrics. (C) 2013 AIP Publishing LLC.

Image deconvolution research: its scope and importance in live cell microscopy

Fluorescence microscopy has become an indispensable tool in cell biology research due its exceptional specificity and ability to visualize subcellular structures with high contrast. It has highest impact when applied in 4D mode, i.e. when applied to record 3D image information as a function of time, since it allows the study of dynamic cellular processes in their native environment. The main issue in 4D fluorescence microscopy is that the phototoxic effect of fluorescence excitation gets accumulated during 4D image acquisition to the extent that normal cell functions are altered. Hence to avoid the alteration of normal cell functioning, it is required to minimize the excitation dose used for individual 2D images constituting a 4D image. Consequently, the noise level becomes very high degrading the resolution. According to the current status of technology, there is a minimum required excitation dose to ensure a resolution that is adequate for biological investigations. This minimum is sufficient to damage light-sensitive cells such as yeast if 4D imaging is performed for an extended period of time, for example, imaging for a complete cell cycle. Nevertheless, our recently developed deconvolution method resolves this conflict forming an enabling technology for visualization of dynamical processes of light-sensitive cells for durations longer than ever without perturbing normal cell functioning. The main goal of this article is to emphasize that there are still possibilities for enabling newer kinds of experiment in cell biology research involving even longer 4D imaging, by only improving deconvolution methods without any new optical technologies.

Sparse Recovery Methods Hold Promise for Diffuse Optical Tomographic Image Reconstruction

The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.