Interface Development for Digitization of Documents Using OCR

The purpose of this thesis is to develop a semi-automated interface that uses Optical Character Recognition (OCR) routines to identify text-based information from a large volume of digitized drawings associated with the oil and gas industry. The identified information is presented in an appropriate interface for any necessary manual modifica- tion, with the target of improving the efficiency of maintaining large amounts of older documents. The thesis outlines the design of the interface and the implementation of Tesseract OCR engine, in combination with tailor-made functions and classes that lever- age OpenCV to enhance the recognition process.The purpose of this thesis is to develop a semi-automated interface that uses Optical Character Recognition (OCR) routines to identify text-based information from a large volume of digitized drawings associated with the oil and gas industry. The identified information is presented in an appropriate interface for any necessary manual modifica- tion, with the target of improving the efficiency of maintaining large amounts of older documents. The thesis outlines the design of the interface and the implementation of Tesseract OCR engine, in combination with tailor-made functions and classes that lever- age OpenCV to enhance the recognition process

Interface Development for Digitization of Documents Using OCR

The purpose of this thesis is to develop a semi-automated interface that uses Optical Character Recognition (OCR) routines to identify text-based information from a large volume of digitized drawings associated with the oil and gas industry. The identified information is presented in an appropriate interface for any necessary manual modification, with the target of improving the efficiency of maintaining large amounts of older documents. The thesis outlines the design of the interface and the implementation of Tesseract OCR engine, in combination with tailor-made functions and classes that leverage OpenCV to enhance the recognition processThe purpose of this thesis is to develop a semi-automated interface that uses Optical Character Recognition (OCR) routines to identify text-based information from a large volume of digitized drawings associated with the oil and gas industry. The identified information is presented in an appropriate interface for any necessary manual modification, with the target of improving the efficiency of maintaining large amounts of older documents. The thesis outlines the design of the interface and the implementation of Tesseract OCR engine, in combination with tailor-made functions and classes that leverage OpenCV to enhance the recognition proces

Learning Model Structure from Data : an Application to On-Line Handwriting

We present a learning strategy for Hidden Markov Models that may be used to cluster handwriting sequences or to learn a character model by identifying its main writing styles. Our approach aims at learning both the structure and parameters of a Hidden Markov Model (HMM) from the data. A byproduct of this learning strategy is the ability to cluster signals and identify allograph. We provide experimental results on artificial data that demonstrate the possibility to learn from data HMM parameters and topology. For a given topology, our approach outperforms in some cases that we identify standard Maximum Likelihood learning scheme. We also apply our unsupervised learning scheme on on-line handwritten signals for allograph clustering as well as for learning HMM models for handwritten digit recognition

Beyond writing: The development of literacy in the Ancient Near East

Previous discussions of the origins of writing in the Ancient Near East have not incorporated the neuroscience of literacy, which suggests that when southern Mesopotamians wrote marks on clay in the late-fourth millennium, they inadvertently reorganized their neural activity, a factor in manipulating the writing system to reflect language, yielding literacy through a combination of neurofunctional change and increased script fidelity to language. Such a development appears to take place only with a sufficient demand for writing and reading, such as that posed by a state-level bureaucracy; the use of a material with suitable characteristics; and the production of marks that are conventionalized, handwritten, simple, and non-numerical. From the perspective of Material Engagement Theory, writing and reading represent the interactivity of bodies, materiality, and brains: movements of hands, arms, and eyes; clay and the implements used to mark it and form characters; and vision, motor planning, object recognition, and language. Literacy is a cognitive change that emerges from and depends upon the nexus of interactivity of the components

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Data display and analysis

Graphical character recognizer and data displa

Feature extraction method for clock drawing test

Recently, the number of elderly persons with dementia has been increasing. In the past, we proposed a dementia evaluation system using daily conversations and developed the system with a conversational robot. However, the current system is not ready for practical use because it can only evaluate time/geographical orientation and short-term memory, and some methods to evaluate other orientations and functions is required as well. In this paper, we discuss a new dementia evaluation system using not only daily conversations but also drawing tests. The authors employed a Clock Drawing Test (CDT) as a new dementia evaluation test and implemented it in a tablet device. This paper discusses a feature extraction and recognition method to distinguish normal cases from dementia cases. After evaluation experiments, the proposed method could recognize 87.6% of the clock drawing images