The deciding role of texture on ductility in a Ce containing Mg alloy

This is the first successful attempt to produce Mg-Ce alloys of different texture through different processing routes while keeping the grain size and grain size distribution same. Tensile data shows that contribution of texture to ductility enhancement is primary and that of grain refinement is secondary. The texture resulting from multi-axial forging of extruded billets followed by annealing exhibits the highest ductility (similar to 40%) at room temperature. (C) 2015 Elsevier B.V. All rights reserved.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Compressed domain human action recognition in H.264/AVC video streams

This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.

Digital image analysis around isotropic points for photoelastic pattern recognition

Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three-and four-point loads. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Activity Recognition in Egocentric Life-Logging Videos

With the increasing availability of wearable cameras, research on first-person view videos (egocentric videos) has received much attention recently. While some effort has been devoted to collecting various egocentric video datasets, there has not been a focused effort in assembling one that could capture the diversity and complexity of activities related to life-logging, which is expected to be an important application for egocentric videos. In this work, we first conduct a comprehensive survey of existing egocentric video datasets. We observe that existing datasets do not emphasize activities relevant to the life-logging scenario. We build an egocentric video dataset dubbed LENA (Life-logging EgoceNtric Activities) (http://people.sutd.edu.sg/similar to 1000892/dataset) which includes egocentric videos of 13 fine-grained activity categories, recorded under diverse situations and environments using the Google Glass. Activities in LENA can also be grouped into 5 top-level categories to meet various needs and multiple demands for activities analysis research. We evaluate state-of-the-art activity recognition using LENA in detail and also analyze the performance of popular descriptors in egocentric activity recognition.

Effect of substrates and surfactants over the evolution of crystallographic texture of nanostructured ZnO thin films deposited through microwave irradiation

In spite of intense research on ZnO over the past decade, the detailed investigation about the crystallographic texture of as obtained ZnO thin films/coatings, and its deviation with growth surface is scarce. We report a systematic study about the orientation distribution of nanostructured ZnO thin films fabricated by microwave irradiation with the variation of substrates and surfactants. The nanostructured films comprising of ZnO nanorods are grown on semiconductor substrates such as Si(100), Ge(100)], conducting substrates (ITO-coated glass, Cr coated Si), and polymer coated Si (PMMA/Si) to examine the respective development of crystallographic texture. The ZnO deposited on semiconductor substrates yieldsmixed texture, whereas c-axis oriented ZnO nanostructured films are obtained by conducting substrate, and PMMA coated Si substrates. Among all the surfactants, nanostructured film produced by using the lower molecular weight of polymeric surfactants (polyvinylpyrrolidone) shows a stronger (0002) texture, and that can be tuned to (10 - 10) by increasing the molecular weight of the surfactant. The strongest basal pole is achieved for the ZnO deposited on PMMA coated Si as substrate, and cetyl-trimethyl ammonium bromide as cationic surfactant. The texture analysis is carried out by X-ray pole figure analysis using the Schultz reflection method. (C) 2015 Elsevier B.V. All rights reserved.

pi-Electron rich small molecule sensors for the recognition of nitroaromatics

Selective and discriminative detection of -NO2 containing high energy organic compounds such as picric acid (PA), 2,4,6-trinitrotoluene (TNT) and dinitrotoluene (DNT) has become a challenging task due to concerns over national security, criminal investigations and environment protections. Among various known detection methods, fluorescence techniques have gained special attention in recent time. A wide variety of fluorescent chemosensors have been developed for nitroaromatic explosive detection. In this review article, we provide an overview of the recent developments made in small molecule-based turn-off fluorescent sensors for nitroaromatic explosives with special focus on organic and H-bonded supramolecular sensors. The fluorescent sensors discussed in this review are classified and organized according to their functionality and their recognition of nitroaromatics by fluorescence quenching.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.

Evolution of Texture and Microstructure in Deformed and Annealed Copper-Iron Multilayer

The effect of multiple phases on the evolution of texture during cold rolling and annealing of a copper-iron multilayer, fabricated by accumulative roll bonding, has been studied. The presence of an iron layer affects the deformation texture of the copper layer only at very large strains. On the other hand, a strong effect of copper on iron is observed at both small and large strains. At smaller strains, the larger deformation carried by the copper suppresses the texture development in the iron, whereas, at higher strains, selection of specific orientation relationship at the interface influences the texture of the iron layer. Shear banding and continuous dynamic recrystallization were found to influence the evolution of texture in the copper layer. The influence of large plastic deformation on the recrystallization behavior of copper is demonstrated with the suppression of typical fcc annealing texture components, described as constrained recrystallization. Evolution of typical annealing texture component is suppressed because of the multilayer microstructure. The plane of the interface formed during deformation is determined by a combination of the rolling texture of individual phases, constrained annealing, and the tendency to form a low-energy interface between the two phases during annealing.

Mechano-fluorochromic Pt-II Luminogen and Its Cysteine Recognition

A new triphenylamine-based organometallic Pt-II luminogen (1) and its analogous organic compound (2) are reported. The molecules are decorated with aldehyde functionality to improve their photophysical properties by utilising donor-acceptor interactions. The single crystal X-ray structure analysis of PtII analogue 1 revealed that the neighbouring molecules were loosely organised by weak intermolecular C-H center dot center dot center dot pi interactions. Because of the twisted nature of the triphenylamine backbone the compounds showed aggregation-induced emission enhancement in THF/water mixture. Due to their loose crystal packing, upon application of external stimuli these luminogens exhibited mechano-fluorochromic behaviour. The crystalline forms of the compounds displayed a more superior emission efficiency than the grinded samples. Moreover, the compounds showed crystallization-induced emission enhancement (CIEE) and exhibited chemodosimetric response towards cysteine under physiological condition.

Maximum Spreading of Liquid Drops Impacting on Groove-Textured Surfaces: Effect of Surface Texture

Maximum, spreading of liquid drops impacting on solid surfaces textured with unidirectional parallel grooves is studied for drop Weber number in the range 1-100 focusing on the role of texture geometry and wettability. The maximum spread factor of impacting drops measured perpendicular to grooves; beta(m,perpendicular to) is seen to be less than, that:measured parallel to grooves, beta(m,perpendicular to).The difference between beta(m,perpendicular to), and beta(m,parallel to) increases with drop impact velocity. This deviation of beta(m,perpendicular to) from beta(m,parallel to) is analyzed by considering the possible mechanisms, correspond, ing to experimental observations (1) impregnation of drop into the grooves, (2) convex shape of liquid vapor interface near contact line at maximum spreading, and (3) contact line pinning of spreading drop at the pillar edges by incorporating them into an energy conservation-based model. The analysis reveals that contact line pinning offers a physically meaningful justification of the observed: deviation of beta(m,perpendicular to) from beta(m,parallel to) compared to other possible candidates. A unified model, incorporating all the above-mentioned mechanisms, is formulated, which predicts beta(m,perpendicular to) on several groove-textured surfaces made of intrinsically hydrophilic and hydrophobic materials with an average error of 8.3%. The effect of groove-texture geometrical parameters,on maximum drop spreading is explained using this unified model. A special case of the unified model, with contact line pinning, absent, predicts beta(m,parallel to) with an average error of 6.3%.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.