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.

What's up with Twitter, in fewer than 10,000 characters

The internet erupted in outrage last week at reports that Twitter is poised to increase the limit for tweets from 140 to 10,000 characters. The first rumours of such a move emerged in the tech news website Re/code back in September then again last week. The response on Twitter was immediate and, for the most part, somewhere between incensed and bemused, with many thousands of tweets posted with hashtags such as #10kTwitter, #Twitter10k, #10000gate, #140twitter, #beyond140 and #longtweets...

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.

Can biological motion be a biometric?

Biological motion has successfully been used for analysis of a person's mood and other psychological traits. Efforts are made to use human gait as a non-invasive mode of biometric. In this reported work, we try to study the effectiveness of biological gait motion of people as a cue to biometric based person recognition. The data is 3D in nature and, hence, has more information with itself than the cues obtained from video-based gait patterns. The high accuracies of person recognition using a simple linear model of data representation and simple neighborhood based classfiers, suggest that it is the nature of the data which is more important than the recognition scheme employed.

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.

Characters of variation of LURR during the earthquake sequence of Xinjiang

The theory of the loading/unloading response ratio (LURR) was applied to the Jiashi earthquake sequence which occurred at the beginning of 1997 in Xinjiang, and found that, before the earthquakes with relatively high magnitudes In the sequence, the ratio showed anomalies of high values. That is to say, the LURR theory can be applied to the short-term earthquake prediction in some cases, especially in the early period after a strong earthquake, such as the forecasts for some strong earthquakes in the Jiashi sequence.

Characters of Surface Deformation and Surface Wave in Thermal Capillary Convection

In the field of fluid mechanics, free surface phenomena is one of the most important physical processes. In the present research work, the surface deformation and surface wave caused by temperature difference of sidewalls in a rectangular cavity have been investigated. The horizontal cross-section of the container is 52 mmx42 mm, and there is a silicon oil layer of height 3.5 mm in the experimental cavity. Temperature difference between the two side walls of the cavity is increased gradually, and the flow on the liquid layer will develop from stable convection to un-stable convection. An optical diagnostic system consisting of a modified Michelson interferometer and image processor has been developed for study of the surface deformation and surface wave of thermal capillary convection. The Fourier transformation method is used to interferometer fringe analysis. The quantitative results of surface deformation and surface wave have been calculated from a serial of the interference fringe patterns.The characters of surface deformation and surface wave have been obtained. They are related with temperature gradient and surface tension. Surface deformation is fluctuant with time, which shows the character of surface wave. The cycle period of the wave is 4.8 s, and the amplitudes are from 0 to 0.55 mu m. The phase of the wave near the cool side of the cavity is opposite and correlative to that near the hot side. The present experiment proves that the surface wave of thermal capillary convection exists on liquid free surface, and it is wrapped in surface deformation.

On Mice and Men and De ratones y hombres: Cultural transfer of substandars characters from literary discourse to film discourse

Eguíluz, Federico; Merino, Raquel; Olsen, Vickie; Pajares, Eterio; Santamaría, José Miguel (eds.)

A study of populations of the anchoveta, Cetengraulis mysticetus, based on meristic characters

ENGLISH: This study was undertaken to determine whether meristic characters indicate that more than one major population of anchovetas occurs in the range of the species from Mexico to Peru. Interest in this species lies in the fact that it is the principal bait fish used to catch yellowfin and skipjack tunas in the Eastern Pacific. Specimens examined were from collections made by California tuna fishing vessels at six major baiting localities covering nearly the entire range of the species, namely, Almejas Bay on the outer coast of Baja California, Guaymas and Ahome Point in the Gulf of California, Gulf of Fonseca, Gulf of Panama, and Gulf of Guayaquil. Four meristic characters were selected for study: vertebrae, dorsal fin rays, anal fin rays, and gill rakers on the first gill arch. Vertebral counts, using X-ray film, were taken from a total of 1,500 fish, 250 each from each of the six localities. For the other characters, 125 anchovetas were examined from each locality for a total of 750, the counts being made with the aid of a binocular microscope. Specimens were between 80 and 165 mm. standard length. SPANISH: Este estudio ha sido hecho con el propósito de determinar si los caracteres numéricos de las anchovetas indican que existe más de una población de este pez en la zona en que se encuentra la especie, comprendida entre México y Perú. El interés en dicha especie radica en el hecho de que éste es el pez de carnada usado principalmente para la pesca de los atunes "aleta amarilla" y "barrilete" en el Pacífico Oriental. Los especímenes que han sido examinados, se tomaron de las muestras recogidas por los barcos atuneros de California en seis de las mejores localidades en que se pesca la anchoveta, las cuales comprenden casi toda la zona en donde se encuentra la especie, a saber, Bahía de Almejas en la costa exterior de Baja California, Guaymas y Punta Ahorne en el Golfo de California, el Golfo de Fonseca, el Golfo de Panamá y el Golfo de Guayaquil. Cuatro caracteres numéricos fueron escogidos para su estudio: los que presentan 1) las vértebras, 2) los radios de la aleta dorsal, 3) los radios de la aleta anal y 4) las branquispinas del primer arco branquial. Mediante el uso de películas con rayos X, se contaron las vértebras en un total de 1,500 peces, es decir, 250 de cada una de las seis mencionadas localidades. En relación con los otros caracteres, se examinaron 125 anchovetas de cada área, o sea, un total de 750 ejemplares, habiendo sido hecho el conteo por medio de un microscopio binocular. Los especímenes tenían un largo standard entre 80 y 165 milímetros. (PDF contains 24 pages.)