18 research outputs found

    Grouping of handwritten Bangla basic characters, numerals and vowel modifiers for multilayer classification

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    This conference paper was presented in the International Conference on Frontiers in Handwriting Recognition, ICFHR 2012; Bari; Italy; 18 September 2012 through 20 September 2012 [© 2012 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/ICFHR.2012.206For better performance in multilayer or hierarchical classification of handwritten text, appropriate grouping of similar symbols is very important. Here we aim to develop a reliable grouping schema for the similar looking basic characters, numerals and vowel modifiers of Bangla language. We experimented with thickened and thinned segmented handwritten text to compare which type of image is better for which group. For classification we chose Support Vector Machine (SVM) as it outperforms other classifiers in this field. We used both "one against one" and "one against all" strategies for multiclass SVM and compared their performance.Publishe

    The use of new technologies to access to handwritten historical information in digital form. Galeón Project

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    Español: La investigación histórica en archivos obliga a realizar un amplio trabajo de revisión de miles de documentos que, en muchos casos, no tienen relación con el tema de estudio, generando un importante gasto en tiempo y recursos. Para dar respuesta a este problema en relación al estudio del patrimonio arqueológico subacuático, desde el CAS-IAPH se ha ideado el Proyecto Galeón, cuyo objetivo es desarrollar soluciones innovadoras para consultar grandes conjuntos digitalizados de documentos históricos manuscritos. Actualmente no es posible la transcripción automatizada de un gran volumen de imágenes de documentos manuscritos, pero el desarrollo tecnológico en el campo del reconocimiento formal de palabras, puede simplificar este proceso. Para ello se ha ideado un modelo teórico de Búsqueda de Palabras Claves (BPC) basado en Grafos de Palabras (GP), que, además de para el patrimonio cultural marítimo, podría utilizarse para otros temas de investigación. Inglés: Historical research in archives forces to realize an extensive work of reviewing thousands of documents that, in many cases, have no connection with the subject matter, generating a significant expenditure of time and resources. To address this problem in relation to the study of underwater archaeological heritage, from the CAS-IAPH has been devised the Galleon Project, which aims to develop innovative solutions to query large sets of historical documents digitized manuscripts. Nowadays It is not possible the automated transcription of a large volume of images from handwritten documents, but the development in the field of formal recognition of words, can simplify this process. For this we have developed a theoretical model to identify Keywords based on Graphs of Words (GP), which, as well as in the maritime cultural heritage, could be used for any research topic

    Drawing, Handwriting Processing Analysis: New Advances and Challenges

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    International audienceDrawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline

    Large vocabulary recognition for online Turkish handwriting with sublexical units

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    We present a system for large vocabulary recognition of online Turkish handwriting, using hidden Markov models. While using a traditional approach for the recognizer, we have identified and developed solutions for the main problems specific to Turkish handwriting recognition. First, since large amounts of Turkish handwriting samples are not available, the system is trained and optimized using the large UNIPEN dataset of English handwriting, before extending it to Turkish using a small Turkish dataset. The delayed strokes, which pose a significant source of variation in writing order due to the large number of diacritical marks in Turkish, are removed during preprocessing. Finally, as a solution to the high out-of-vocabulary rates encountered when using a fixed size lexicon in general purpose recognition, a lexicon is constructed from sublexical units (stems and endings) learned from a large Turkish corpus. A statistical bigram language model learned from the same corpus is also applied during the decoding process. The system obtains a 91.7% word recognition rate when tested on a small Turkish handwritten word dataset using a medium sized (1950 words) lexicon corresponding to the vocabulary of the test set and 63.8% using a large, general purpose lexicon (130,000 words). However, with the proposed stem+ending lexicon (12,500 words) and bigram language model with lattice expansion, a 67.9% word recognition accuracy is obtained, surpassing the results obtained with the general purpose lexicon while using a much smaller one

    Text Extraction from Historical Document Images by the Combination of Several Thresholding Techniques

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    This paper presents a new technique for the binarization of historical document images characterized by deteriorations and damages making their automatic processing difficult at several levels. The proposed method is based on hybrid thresholding combining the advantages of global and local methods and on the mixture of several binarization techniques. Two stages have been included. In the first stage, global thresholding is applied on the entire image and two different thresholds are determined from which the most of image pixels are classified into foreground or background. In the second stage, the remaining pixels are assigned to foreground or background classes based on local analysis. In this stage, several local thresholding methods are combined and the final binary value of each remaining pixel is chosen as the most probable one. The proposed technique has been tested on a large collection of standard and synthetic documents and compared with well-known methods using standard measures and was shown to be more powerful

    Representation, Recognition and Collaboration with Digital Ink

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    Pen input for computing devices is now widespread, providing a promising interaction mechanism for many purposes. Nevertheless, the diverse nature of digital ink and varied application domains still present many challenges. First, the sampling rate and resolution of pen-based devices keep improving, making input data more costly to process and store. At the same time, existing applications typically record digital ink either in proprietary formats, which are restricted to single platforms and consequently lack portability, or simply as images, which lose important information. Moreover, in certain domains such as mathematics, current systems are now achieving good recognition rates on individual symbols, in general recognition of complete expressions remains a problem due to the absence of an effective method that can reliably identify the spatial relationships among symbols. Last, but not least, existing digital ink collaboration tools are platform-dependent and typically allow only one input method to be used at a time. Together with the absence of recognition, this has placed significant limitations on what can be done. In this thesis, we investigate these issues and make contributions to each. We first present an algorithm that can accurately approximate a digital ink curve by selecting a certain subset of points from the original trace. This allows a compact representation of digital ink for efficient processing and storage. We then describe an algorithm that can automatically identify certain important features in handwritten symbols. Identifying the features can help us solve a number of problems such as improving two-dimensional mathematical recognition. Last, we present a framework for multi-user online collaboration in a pen-based and graphical environment. This framework is portable across multiple platforms and allows multimodal interactions in collaborative sessions. To demonstrate our ideas, we present InkChat, a whiteboard application, which can be used to conduct collaborative sessions on a shared canvas. It allows participants to use voice and digital ink independently and simultaneously, which has been found useful in remote collaboration

    A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

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    People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

    An intelligent framework for pre-processing ancient Thai manuscripts on palm leaves

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    In Thailand’s early history, prior to the availability of paper and printing technologies, palm leaves were used to record information written by hand. These ancient documents contain invaluable knowledge. By digitising the manuscripts, the content can be preserved and made widely available to the interested community via electronic media. However, the content is difficult to access or retrieve. In order to extract relevant information from the document images efficiently, each step of the process requires reduction of irrelevant data such as noise or interference on the images. The pre-processing techniques serve the purpose of extracting regions of interest, reducing noise from the image and degrading the irrelevant background. The image can then be directly and efficiently processed for feature selection and extraction prior to the subsequent phase of character recognition. It is therefore the main objective of this study to develop an efficient and intelligent image preprocessing system that could be used to extract components from ancient manuscripts for information extraction and retrieval purposes. The main contributions of this thesis are the provision and enhancement of the region of interest by using an intelligent approach for the pre-processing of ancient Thai manuscripts on palm leaves and a detailed examination of the preprocessing techniques for palm leaf manuscripts. As noise reduction and binarisation are involved in the first step of pre-processing to eliminate noise and background from image documents, it is necessary for this step to provide a good quality output; otherwise, the accuracy of the subsequent stages will be affected. In this work, an intelligent approach to eliminate background was proposed and carried out by a selection of appropriate binarisation techniques using SVM. As there could be multiple binarisation techniques of choice, another approach was proposed to eliminate the background in this study in order to generate an optimal binarised image. The proposal is an ensemble architecture based on the majority vote scheme utilising local neighbouring information around a pixel of interest. To extract text from that binarised image, line segmentation was then applied based on the partial projection method as this method provides good results with slant texts and connected components. To improve the quality of the partial projection method, an Adaptive Partial Projection (APP) method was proposed. This technique adjusts the size of a character strip automatically by adapting the width of the strip to separate the connected component of consecutive lines through divide and conquer, and analysing the upper vowels and lower vowels of the text line. Finally, character segmentation was proposed using a hierarchical segmentation technique based on a contour-tracing algorithm. Touching components identified from the previous step were then separated by a trace of the background skeletons, and a combined method of segmentation. The key datasets used in this study are images provided by the Project for Palm Leaf Preservation, Northeastern Thailand Division, and benchmark datasets from the Document Image Binarisation Contest (DIBCO) series are used to compare the results of this work against other binarisation techniques. The experimental results have shown that the proposed methods in this study provide superior performance and will be used to support subsequent processing of the Thai ancient palm leaf documents. It is expected that the contributions from this study will also benefit research work on ancient manuscripts in other languages
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