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Mobile System for Text Recognition on Android
Tomešek, Jan ; Kolář, Martin (referee) ; Zemčík, Pavel (advisor)
This thesis deals with creation of a mobile library for preprocessing of images with text which represents a part of a system for text recognition. The library is realized with emphasis on generality of use, efficiency and portability. The library providing a set of algorithms primarily for image quality assessment and text detection was created in this thesis. These algorithms enable a substantial decrease in volume of transmitted data and speed up and refinement of the recognition process. An example application for the Android platform able to analyze composition of foods stated on their wrappings was created as well. Overall, the library (system) simplifies development of mobile applications with focus on text extraction and analysis. The mobile application then provides a comfortable way of food harmfulness verification. The thesis offers a reader an overview of current solutions and tools available in this field, it provides a breakdown of important image preprocessing algorithms and guides him through the construction of the library and the application for mobile devices.
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Data extraction from document scans
Macháč, Bohuslav ; Kolomazník, Jan (advisor) ; Krajíček, Václav (referee)
In this work I developed an application capable of extracting data from scanned documents. For optical character recognition, I used external OCR engine Tesseract, but it can be easily changed. I use document templates, which have informations about data areas and its data types. I tried to automatize most of the steps which are required to extract data or create new data template. User can improve or change results of these steps. For export from application I implemented components, which export data to XML, HTML or plain text. Another components can be easily added, to adapt application for various uses.
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Optical Character Recognition
Suchý, Václav ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This paper describes problems of text recognition in picture. Discuss successes, advatages and disadvantages several methods of recognition. In second part there is described design and implementation of a simple OCR software for typewritten text recognition by using artificial neural networks.
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Hand Writing Letters Recognition
Jelínek, Radek ; Žák, Jakub (referee) ; Zbořil, František (advisor)
The thesis deals with handwriting recognition and conversion into digital form. Recognition is focused on recognition of letters and finding success when you did not use the dictionary for word recognition. One part of document is compare with commercial applications.
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Recognition of Handwriting for Mobile Phones
Talaš, Vladimír ; Chalupníček, Kamil (referee) ; Schwarz, Petr (advisor)
The goal of this project is to create a mobile phone application, which can use phone camera to get a photography. This photography contains text, application has an ability to find a text, recognize all characters and send output as SMS. In this application there are implemented algorithms for text recognize from pictures based on Hidden Markovov Models. The particular stress is put on training of the model, to maximalise a succes of text recognition. There are some experiments model training with model variables, which are leading in better ability of text recognition. It was achieved a value of 97% succesfully recognized characters.
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Sudoku Solver for Android
Hrbas, Vojtěch ; Herout, Adam (referee) ; Páldy, Alexander (advisor)
This work deals with solving Sudoku game which is taken by a camera of a mobile device running Android. It discusses possibilities of image processing, possibilities of recognizing the text in the image and principle and solving of Sudoku game. It also examines existing applications for Android that solve Sudoku. Then it proposes the application itself for solving Sudoku and summarizes the results of testing the application in terms of performance and users.
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Automatic Text Recognition for Robots
Hartman, Zdeněk ; Materna, Zdeněk (referee) ; Španěl, Michal (advisor)
This bachelor thesis describe module design for text detection and recognition for use in robotic systems. To detect charters is used Stroke Width transform, which is applied on the input edge image. In the output image after Stroke Width transform are found connected components. For letter grouping into a words is used Hough transform, which is applied on the created binary image. This image contains points, which corresponding positions of found connected components. To recognize signs in detected areas is used Tesseract library. Before recognition detected areas are extracted and rotated into a horizontal position. This proposed detector can detect even rotated text. Accuracy of detection of the text is 75% above the test set "informační tabule".
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Social Network Analysis using methods of pattern recognition
Križan, Viliam ; Burget, Radim (referee) ; Atassi, Hicham (advisor)
Diplomová práca sa zaoberá rozpoznávaním emócií z textu v sociálnych sieťach. Práca popisuje súčasné metódy extrakcie príznakov, používané lexikóny, korpusy a klasifikátory. Emócie boli rozpoznávané na základe klasifikátoru, netrénovaného na anotovaných dátach z mikroblogovacej siete Twitter. Výhodou použitia služby Twitter, bolo geografické vymedzenie dát, ktoré umožňuje sledovanie zmien emócií populácie v rôznych mestách. Prvým prístupom klasifikácie bolo vytvorenie Baseline algoritmu, ktorý používal jednoduchý lexikón. Pre zlepšenie klasifikácie sme v druhom bode použili komplexnejší SVM klasifikátor. SVM klasifikátory, extrakcie a selekcie príznakov boli použité z dostupnej Python knižnice Scikit. Dáta pre natrénovanie klasifikátoru boli zhromažďované z oblasti USA, a to s pomocou vytvorenej aplikácie. Klasifikátor bol natrénovaný na dátach, označených pri ich zhromažďovaní - bez manuálnej anotácie. Boli použité dve rôzne implantácie SVM klasifikátorov. Výsledné klasifikované emócie, v rôznych mestách a dňoch, boli zobrazené v podobe farebných značiek na mape.
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