Predspracovanie obrazu pre optické rozpoznávanie ... - TUKE

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FEI TU v Košiciach Diplomová práca List č. 86 - activation function: f(xi)= 1 1+e −λ∗x i Note that parameters M and N were determined by experiments. The ’Image PreProcessing’ application was designed for the purpose of image preprocessing using neural networks, the workflow chart is shown on the picture 48. The application can be done in three different ways: - fully automatic application - half-automatic application - manualy controled application On the picture 48 are two boxes which are affected by these three different ways. Determine background and foreground combination is done automaticaly in the concept of fully automatic and half-automatic aplica- tions and it would require some logic to compare the current foreground and background to known combinations of foreground and background (this could be done by modular neural network). Create training and testing pattern would need computer vision and OCR itself to determine the text on the original picture, that’s why it is automatic only in the concept of fully automatic application. Because the main target of this masters thesis was to do research on image preprocessing using neural networks and not to make the best preprocessing application, I decided to use the concept of manualy controled application for my ’Image PreProcessor’. This way user has to input the text he sees on the picture and place the text exactly over the text on the picture and then the application can create the training and testing pattern. You can see a screenshot from the ’Image PreProcessor’ on the picture 49. Experiments Some experiments must have been realised to determine some parameters of the Image PreProcessing system and its neural network. On more scan- ned documents I have found 25 different combinations of background and
FEI TU v Košiciach Diplomová práca List č. 87 START Load Image Convert shades of gray to floating point numbers Determine background and foreground combination Do we have NN trained? Process image STOP yes Load NN weights Convert floating point numbers to shades of gray Save image no Create training and testing pattern Train NN Save NN weights Obr. 48: Workflow chart of Image PreProcessing application.
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Technická univerzita v Košiciach
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Poďakovanie Chcem poďakovať môj
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Thesis title: Image preprocessing f
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Obsah Formulácia úlohy 1 1 Úvod
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FEI TU v Košiciach Diplomová prá
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Predspracovanie obrazu pre optické rozpoznávanie ... - TUKE

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