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Character recognition of machine-written documents
Kindermann, Hubert ; Blažek, Jan (advisor) ; Kolomazník, Jan (referee)
In the present thesis we solve the problem of symbol extraction and recognition from printed documents digitized by the scanner or camera. We introduce a noise resistant algorithm of document lighting normalization. We continue with the extraction of individual characters from the document and their recognition with a system of feedforward multilayer neural networks. We also focus on processing of the resulting set of recognized characters, which is necessary for further use of the extracted text. The last step is correction of the output based on surrounding letters of each character. We have successfully implemented an automatic system containing all the above components.
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Handwriting recognition using neural network
Petr, Martin ; Surynek, Pavel (advisor) ; Pergel, Martin (referee)
Title: Handwriting recognition using neural network Author: Martin Petr Department: Department of Theoretical Computer Science and Mathematical Logic Supervisor: RNDr. Pavel Surynek, PhD. Supervisor's e-mail address: pavel.surynek@mff.cuni.cz Abstract: Pattern recognition finds its use in many fields whose development has been affected by computer science and computer technology. Among these, the conversion of handwritten or printed text into computer-encoded text has a particularly prominent position. In the presented work we propose a method for recognizing handwritten characters in real-time using feedforward neural network as the basic classification mechanism. Dealing with differences among individual instances of each handwritten character we thoroughly explored the possibility of suppressing these while emphasizing characteristics that are essential for successful recognition. For these purposes we employed discrete cosine transform, whose time-proven application in audio and video signal processing or even directly in the field of pattern recognition provided a convincing argument for us to use it in our work as well. As a means of suppressing variations among various writing instruments we proposed preprocessing of input images using binarization and skeletonization. The designed method was...
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Automatic Invoice Recognition and Processing
Ščešňák, Vladimír ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This work aims to design and implement application for automatic recognition and processing invoices with assistance using computer vision. The work deals with the analysis of existing invoices, design and implementation of an algorithm for correctly recognition, selection of appropriate test patterns and also design and implementation of the user interface.
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License Plate Detection and Recognition from Still Image
Janíček, Kryštof ; Sochor, Jakub (referee) ; Špaňhel, Jakub (advisor)
This thesis describes the design and implementation of system for detection and recognition of license plate. This system is divided into three parts which are license plate detection, character segmentation and optical character recognition. License plate detection is done by cascade classifier that achieves hit rate of 95.5% and precision rate of 95.9%. Character segmentation is based on contour finding that achieves hit rate of 93.3% and precision rate of 96.5%. Optical character recognition is done by neural network and achieves hit rate of 98.4% for individual characters. The whole system is able to detect and recognize up to 81.5% of license plates from the test data set.
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Section Speed Measurement for Traffic Analysis
Kubíčková, Pavla ; Špaňhel, Jakub (referee) ; Sochor, Jakub (advisor)
This bachelor thesis focuses on section speed measurement for traffic analysis. This thesis desribes existing methods of detection of license plates and classification of their characters. Methods of cascade classifier and classifier SVM are described in this work. Evaluation of individual parts of the system is processed in the final section.
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Picture analysis and comparing
Novotný, Václav ; Nováček, Petr (referee) ; Richter, Miloslav (advisor)
This bachelor thesis concerns about analysis and image correlation. It discusses possibilities of image processing and hardware data collection system. Image database is created and algorithms for processing and comparing acquired images with reference are designed and created in this thesis.
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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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Recognition of Vehicle Number Plates
Martinský, Ondrej ; Zbořil, František (referee) ; Zbořil, František (advisor)
This work deals with problematic from field of artificial intelligence, machine vision and neural networks in construction of an automatic number plate recognition system. (ANPR). This problematic includes mathematical principles and algorithms, which ensure a process of number plate detection, processes of proper characters segmentation, normalization and recognition. Work comparatively deals with methods achieving invariance of systems towards image skew, translations and various light conditions during the capture. Work also contains an implementation of a demonstration model, which is able to proceed these functions over a set of snapshots.
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Optical Character Recognition
Pokorný, Pavel ; Juránek, Roman (referee) ; Mlích, Jozef (advisor)
This paper presents some of the methods for locating and recognizing text in an image document. It describes feature extraction issues and commonly used machine learning algorithms. In the latest part, there is description of design and implementation of application for printed text recognition.
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Car Licence Plate Detection and Recognition
Kovaříček, Roman ; Procházka, Boris (referee) ; Váňa, Jan (advisor)
This bachelor thesis deals with finding the license plates in the image and pattern recognition. Work describes short history of the state license plates. It deals with also the current state license plates and their problems. It analyzes the process of image segmentation and follow evaluation of selected areas. A part of the work is design and implementation of algorithms that solve candidate search areas or characters. The final step is the recognition of individual characters and display the user with details of the result.
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