SEGMENTATION OF NON-TEXT FROM BILINGUAL REAL-TIME OFFICE DOCUMENT IMAGES USING U-NET ARCHITECTURE
SHIVAKUMAR GRAVIKUMAR MSAMPATHKUMAR SSHIVAPRASAD B J
Abstract
Abstract In this work, we have presented an efficient approach for segmentation of non-text document information from real time office document images which are bilingual using a machine learning approach i.e., U-net architecture for experimentation purpose. We have created our own dataset containing 200 document images. Initially pre-processing is applied on the input document images proposed method is compared with other existing methods and obtained accuracy of 99% different performance measure i.e., (Specificity, Sensitivity, Precision, F1-Score) used in the experimentation.
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