Dynamic Space Warping Of Strokes For Recognition Of Online Handwritten Characters

This paper suggests a scheme for classifying online handwritten characters, based on dynamic space warping of strokes within the characters. A method for segmenting components into strokes using velocity profiles is proposed. Each stroke is a simple arbitrary shape and is encoded using three attributes. Correspondence between various strokes is established using Dynamic Space Warping. A distance measure which reliably differentiates between two corresponding simple shapes (strokes) has been formulated thus obtaining a perceptual distance measure between any two characters. Tests indicate an accuracy of over 85% on two different datasets of characters.

Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms

This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of ldquogoodrdquo features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.

Fusion of Complementary Online and Offline Strategies for Recognition of Handwritten Kannada Characters

This work describes an online handwritten character recognition system working in combination with an offline recognition system. The online input data is also converted into an offline image, and parallely recognized by both online and offline strategies. Features are proposed for offline recognition and a disambiguation step is employed in the offline system for the samples for which the confidence level of the classifier is low. The outputs are then combined probabilistically resulting in a classifier out-performing both individual systems. Experiments are performed for Kannada, a South Indian Language, over a database of 295 classes. The accuracy of the online recognizer improves by 11% when the combination with offline system is used.

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.

Phenotypic characters of rice landraces reveal independent lineages of short-grain aromatic indica rice

Rice landraces are lineages developed by farmers through artificial selection during the long-term domestication process. Despite huge potential for crop improvement, they are largely understudied in India. Here, we analyse a suite of phenotypic characters from large numbers of Indian landraces comprised of both aromatic and non-aromatic varieties. Our primary aim was to investigate the major determinants of diversity, the strength of segregation among aromatic and non-aromatic landraces as well as that within aromatic landraces. Using principal component analysis, we found that grain length, width and weight, panicle weight and leaf length have the most substantial contribution. Discriminant analysis can effectively distinguish the majority of aromatic from non-aromatic landraces. More interestingly, within aromatic landraces long-grain traditional Basmati and short-grain non-Basmati aromatics remain morphologically well differentiated. The present research emphasizes the general patterns of phenotypic diversity and finds out the most important characters. It also confirms the existence of very unique short-grain aromatic landraces, perhaps carrying signatures of independent origin of an additional aroma quantitative trait locus in the indica group, unlike introgression of specific alleles of the BADH2 gene from the japonica group as in Basmati. We presume that this parallel origin and evolution of aroma in short-grain indica landraces are linked to the long history of rice domestication that involved inheritance of several traits from Oryza nivara, in addition to O. rufipogon. We conclude with a note that the insights from the phenotypic analysis essentially comprise the first part, which will likely be validated with subsequent molecular analysis.

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.

CCD: Connected Component Descriptor for Robust Mosaicing of Camera-Captured Document Images

We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.

New species of Ptychozoon (Sauria: Gekkonidae) from the Nicobar Archipelago, Indian Ocean

A new species of Ptychozoon is described from the central portion of the Nicobar Archipelago, Bay of Bengal, India. It has been formerly referred to P. kuhli, a species widely distributed in Sundaland. Ptychozoon nicobarensis sp. nov. reaches an SVL of 100.3 mm, and is diagnosable from congeneric species in showing the following combination of characters: dorsum with a tan vertebral stripe, lacking dark transverse bars; supranasals in contact; cutaneous expansions on sides of head; absence of predigital notch in preantebrachial cutaneous expansion; imbricate parachute support scales; four irregular rows of low, rounded enlarged scales on dorsum; 20-29 scales across widest portion of tail terminus; three indistinct chevrons on dorsum; 7-11 pairs of preanal pores; femoral pores absent; tail with an expanded terminal flap and weak lobe fusion at proximal border of tail terminus. The curious distribution of the new species, centred around the central Nicobars is speculated to be the result of competition with and/or predation by large gekkonid species, to the north (Gekko verreauxi) and south (G. smithii) of the group of islands occupied by the new Ptychozoon from the central Nicobars.

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Zeeman effect of nuclear quadrupole resonance in 1-chloro-2,4-dinitrobenzene

The Zeeman effect of NQR was studied in 1-chloro-2,4-dinitrobenzene. A low value of the asymmetry parameter (0.10) was obtained. Four physically inequivalent field gradients were located and their orientations in the crystallographic abc system were determined using symmetry considerations. From these data the orientations of the molecules in the unit cell were determined. The results agree well with the two-dimensional x-ray structural data. The bond characters of the C[Single Bond]Cl bond were calculated, and the values compare well with those generally obtained for C[Single Bond]Cl bonds in chlorine derivatives of benzene. ©1973 The American Institute of Physics.

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Molecular phylogeny and biogeography of langurs and leaf monkeys of South Asia (Primates: Colobinae)

The two recently proposed taxonomies of the langurs and leaf monkeys (Subfamily Colobinae) provide different implications to our understanding of the evolution of Nilgiri and purple-faced langurs. Groves (2001) [Groves, C.P., 2001. Primate Taxonomy. Smithsonian Institute Press, Washington], placed Nilgiri and purple-faced langurs in the genus Trachypithecus, thereby suggesting disjunct distribution of the genus Trachypithecus. [Brandon-Jones, D., Eudey, A.A., Geissmann, T., Groves, C.P., Melnick, D.J., Morales, J.C., Shekelle, M., Stewart, C.-B., 2003. Asian primate classification. Int. J. Primatol. 25, 97–162] placed these langurs in the genus Semnopithecus, which suggests convergence of morphological characters in Nilgiri and purple-faced langurs with Trachypithecus. To test these scenarios, we sequenced and analyzed the mitochondrial cytochrome b gene and two nuclear DNA-encoded genes, lysozyme and protamine P1, from a variety of colobine species. All three markers support the clustering of Nilgiri and purple-faced langurs with Hanuman langur (Semnopithecus), while leaf monkeys of Southeast Asian (Trachypithecus) form a distinct clade. The phylogenetic position of capped and golden leaf monkeys is still unresolved. It is likely that this species group might have evolved due to past hybridization between Semnopithecus and Trachypithecus clades.

Raman effect of corundum

The Raman effect of corundum (sapphire) was measured with an Ar+ laser source. The seven expected Raman active phonons were found and their symmetry characters determined. Assignment of the internal and external vibrations of the crystals was made and the effect of birefringence in the Raman selection rules is discussed.