Recognition of Kannada characters extracted from scene images

In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

Language models for online handwritten Tamil word recognition

N-gram language models and lexicon-based word-recognition are popular methods in the literature to improve recognition accuracies of online and offline handwritten data. However, there are very few works that deal with application of these techniques on online Tamil handwritten data. In this paper, we explore methods of developing symbol-level language models and a lexicon from a large Tamil text corpus and their application to improving symbol and word recognition accuracies. On a test database of around 2000 words, we find that bigram language models improve symbol (3%) and word recognition (8%) accuracies and while lexicon methods offer much greater improvements (30%) in terms of word recognition, there is a large dependency on choosing the right lexicon. For comparison to lexicon and language model based methods, we have also explored re-evaluation techniques which involve the use of expert classifiers to improve symbol and word recognition accuracies.

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.

A cyclic peptide mimic of an RNA recognition motif of human La protein is a potent inhibitor of hepatitis C virus

Due to limited available therapeutic options, developing new lead compounds against hepatitis C virus is an urgent need. Human La protein stimulates hepatitis C virus translation through interaction with the hepatitis C viral RNA. A cyclic peptide mimicking the beta-turn of the human La protein that interacts with the viral RNA was synthesized. It inhibits hepatitis C viral RNA translation significantly better than the corresponding linear peptide at longer post-treatment times. The cyclic peptide also inhibited replication as measured by replicon RNA levels using real time RT-PCR. The cyclic peptide emerges as a promising lead compound against hepatitis C.

Natural motion of one-dimensional flexible objects using minimization approaches

For one-dimensional flexible objects such as ropes, chains, hair, the assumption of constant length is realistic for large-scale 3D motion. Moreover, when the motion or disturbance at one end gradually dies down along the curve defining the one-dimensional flexible objects, the motion appears ``natural''. This paper presents a purely geometric and kinematic approach for deriving more natural and length-preserving transformations of planar and spatial curves. Techniques from variational calculus are used to determine analytical conditions and it is shown that the velocity at any point on the curve must be along the tangent at that point for preserving the length and to yield the feature of diminishing motion. It is shown that for the special case of a straight line, the analytical conditions lead to the classical tractrix curve solution. Since analytical solutions exist for a tractrix curve, the motion of a piecewise linear curve can be solved in closed-form and thus can be applied for the resolution of redundancy in hyper-redundant robots. Simulation results for several planar and spatial curves and various input motions of one end are used to illustrate the features of motion damping and eventual alignment with the perturbation vector.

Factors influencing stick-slip motion: effect of hardness, crystal structure and surface texture

In the present investigation, efforts were made to study the different frictional responses of materials with varying crystal structure and hardness during sliding against a relatively harder material of different surface textures and roughness. In the experiments, pins were made of pure metals and alloys with significantly different hardness values. Pure metals were selected based on different class of crystal structures, such as face centered cubic (FCC), body centered cubic (BCC), body centered tetragonal (BCT) and hexagonal close packed (HCP) structures. The surface textures with varying roughness were generated on the counterpart plate which was made of H-11 die steel. The experiments were conducted under dry and lubricated conditions using an inclined pin-on-plate sliding tester for various normal loads at ambient environment. In the experiments, it was found that the coefficient of friction is controlled by the surface texture of the harder mating surfaces. Further, two kinds of frictional response, namely steady-state and stick-slip, were observed during sliding. More specifically, stead-state frictional response was observed for the FCC metals, alloys and materials with higher hardness. Stick-slip frictional response was observed for the metals which have limited number of slip systems such as BCT and HCP. In addition, the stick-slip frictional response was dependent on the normal load, lubrication, hardness and surface texture of the counterpart material. However, for a given kind of surface texture, the roughness of the surface affects neither the average coefficient of friction nor the amplitude of stick-slip oscillation significantly.

Ground motion prediction equation considering combined dataset of recorded and simulated ground motions

Himalayan region is one of the most active seismic regions in the world and many researchers have highlighted the possibility of great seismic event in the near future due to seismic gap. Seismic hazard analysis and microzonation of highly populated places in the region are mandatory in a regional scale. Region specific Ground Motion Predictive Equation (GMPE) is an important input in the seismic hazard analysis for macro- and micro-zonation studies. Few GMPEs developed in India are based on the recorded data and are applicable for a particular range of magnitudes and distances. This paper focuses on the development of a new GMPE for the Himalayan region considering both the recorded and simulated earthquakes of moment magnitude 5.3-8.7. The Finite Fault simulation model has been used for the ground motion simulation considering region specific seismotectonic parameters from the past earthquakes and source models. Simulated acceleration time histories and response spectra are compared with available records. In the absence of a large number of recorded data, simulations have been performed at unavailable locations by adopting Apparent Stations concept. Earthquakes recorded up to 2007 have been used for the development of new GMPE and earthquakes records after 2007 are used to validate new GMPE. Proposed GMPE matched very well with recorded data and also with other highly ranked GMPEs developed elsewhere and applicable for the region. Comparison of response spectra also have shown good agreement with recorded earthquake data. Quantitative analysis of residuals for the proposed GMPE and region specific GMPEs to predict Nepal-India 2011 earthquake of Mw of 5.7 records values shows that the proposed GMPE predicts Peak ground acceleration and spectral acceleration for entire distance and period range with lower percent residual when compared to exiting region specific GMPEs. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

A two-axis in-plane motion measurement system based on optical beam deflection

Measurement of in-plane motion with high resolution and large bandwidth enables model-identification and real-time control of motion-stages. This paper presents an optical beam deflection based system for measurement of in-plane motion of both macro- and micro-scale motion stages. A curved reflector is integrated with the motion stage to achieve sensitivity to in-plane translational motion along two axes. Under optimal settings, the measurement system is shown to theoretically achieve sub-angstrom measurement resolution over a bandwidth in excess of 1 kHz and negligible cross-sensitivity to linear motion. Subsequently, the proposed technique is experimentally demonstrated by measuring the in-plane motion of a piezo flexure stage and a scanning probe microcantilever. For the former case, reflective spherical balls of different radii are employed to measure the in-plane motion and the measured sensitivities are shown to agree with theoretical values, on average, to within 8.3%. For the latter case, a prototype polydimethylsiloxane micro-reflector is integrated with the microcantilever. The measured in-plane motion of the microcantilever probe is used to identify nonlinearities and the transient dynamics of the piezo-stage upon which the probe is mounted. These are subsequently compensated by means of feedback control. (C) 2013 AIP Publishing LLC.

NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images

In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

STUDENT'S-t MIXTURE MODEL BASED MULTI-INSTRUMENT RECOGNITION IN POLYPHONIC MUSIC

We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.

H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV)

In this paper, we have proposed a simple and effective approach to classify H.264 compressed videos, by capturing orientation information from the motion vectors. Our major contribution involves computing Histogram of Oriented Motion Vectors (HOMV) for overlapping hierarchical Space-Time cubes. The Space-Time cubes selected are partially overlapped. HOMV is found to be very effective to define the motion characteristics of these cubes. We then use Bag of Features (B OF) approach to define the video as histogram of HOMV keywords, obtained using k-means clustering. The video feature, thus computed, is found to be very effective in classifying videos. We demonstrate our results with experiments on two large publicly available video database.

Constrained 3D sketching with haptics and active motion annotation

The aim of this work is to enable seamless transformation of product concepts to CAD models. This necessitates availability of 3D product sketches. The present work concerns intuitive generation of 3D strokes and intrinsic support for space sharing and articulation for the components of the product being sketched. Direct creation of 3D strokes in air lacks in precision, stability and control. The inadequacy of proprioceptive feedback for the task is complimented in this work with stereo vision and haptics. Three novel methods based on pencil-paper interaction analogy for haptic rendering of strokes have been investigated. The pen-tilt based rendering is simpler and found to be more effective. For the spatial conformity, two modes of constraints for the stylus movements, corresponding to the motions on a control surface and in a control volume have been studied using novel reactive and field based haptic rendering schemes. The field based haptics, which in effect creates an attractive force field near a surface, though non-realistic, provided highly effective support for the control-surface constraints. The efficacy of the reactive haptic rendering scheme for the constrained environments has been demonstrated using scribble strokes. This can enable distributed collaborative 3D concept development. The notion of motion constraints, defined through sketch strokes enables intuitive generation of articulated 3D sketches and direct exploration of motion annotations found in most product concepts. The work, thus, establishes that modeling of the constraints is a central issue in 3D sketching.

Common recognition principles across diverse sequence and structural families of sialic acid binding proteins

Sialic acids form a large family of 9-carbon monosaccharides and are integral components of glycoconjugates. They are known to bind to a wide range of receptors belonging to diverse sequence families and fold classes and are key mediators in a plethora of cellular processes. Thus, it is of great interest to understand the features that give rise to such a recognition capability. Structural analyses using a non-redundant data set of known sialic acid binding proteins was carried out, which included exhaustive binding site comparisons and site alignments using in-house algorithms, followed by clustering and tree computation, which has led to derivation of sialic acid recognition principles. Although the proteins in the data set belong to several sequence and structure families, their binding sites could be grouped into only six types. Structural comparison of the binding sites indicates that all sites contain one or more different combinations of key structural features over a common scaffold. The six binding site types thus serve as structural motifs for recognizing sialic acid. Scanning the motifs against a non-redundant set of binding sites from PDB indicated the motifs to be specific for sialic acid recognition. Knowledge of determinants obtained from this study will be useful for detecting function in unknown proteins. As an example analysis, a genome-wide scan for the motifs in structures of Mycobacterium tuberculosis proteome identified 17 hits that contain combinations of the features, suggesting a possible function of sialic acid binding by these proteins.

Triarylborane-Appended New Triad and Tetrad: Chromogenic and Fluorogenic Anion Recognition

Facile synthesis of triad 3 and tetrad 4 incorporating -B(Mes)(2) (Mes = mesityl (2,4,6-trimethylphenyl)), boron dipyrromethene (BODIPY), and triphenylamine is reported. Introduction of two dissimilar acceptors (triarylborane and BODIPY) on a single donor resulted in two distinct intramolecular charge transfer processes (amine-to-borane and amine-to-BODIPY). The absorption and emission properties of the new triad and tetrad are highly dependent on individual building units. The nature of electronic communication among the individual fluorophore units has been comprehensively investigated and compared with building units. Compounds 3 and 4 showed chromogenic and fluorogenic responses for small anions such as fluoride and cyanide.

Dual Binding Site Assisted Chromogenic and Fluorogenic Recognition and Discrimination of Fluoride and Cyanide by a Peripherally Borylated Metalloporphyrin: Overcoming Anion Interference in Organoboron Based Sensors

Peripherally triarylborane decorated porphyrin (2) and its Zn(II) complex (3) have been synthesized. Compound 3 contains of two different Lewis acidic binding sites (Zn(II) and boron center). Unlike all previously known triarylborane based sensors, the optical responses of 3 toward fluoride and cyanide are distinctively different, thus enabling the discrimination of these two interfering anions. Metalloporphyrin 3 shows a multiple channel fluorogenic response toward fluoride and cyanide and also a selective visual colorimetric response toward cyanide. By comparison with model systems and from detailed photophysical studies on 2 and 3, we conclude that the preferential binding of fluoride occurs at the peripheral borane moieties resulting in the cessation of the EET (electronic energy transfer) process from borane to porphyrin core and with negligible negetive cooperative effects. On the other hand, cyanide binding occurs at the Zn(II) core leading to drastic changes in its absorption behavior which can be followed by the naked eye. Such changes are not observed when the boryl substituent is absent (e.g., Zn-TPP and TPP). Compounds 2 and 3 were also found to be capable of extracting fluoride from aqueous medium.