期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2015
卷号：6
期号：4
页码：57
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The paper addresses the automation of the task of an epigraphist in reading and deciphering inscriptions.The automation steps include Pre-processing, Segmentation, Feature Extraction and Recognition. Preprocessinginvolves, enhancement of degraded ancient document images which is achieved through Spatialfiltering methods, followed by binarization of the enhanced image. Segmentation is carried out using DropFall and Water Reservoir approaches, to obtain sampled characters. Next Gabor and Zonal features areextracted for the sampled characters, and stored as feature vectors for training. Artificial Neural Network(ANN) is trained with these feature vectors and later used for classification of new test characters. Finallythe classified characters are mapped to characters of modern form. The system showed good results whentested on the nearly 150 samples of ancient Kannada epigraphs from Ashoka and Hoysala periods. Anaverage Recognition accuracy of 80.2% for Ashoka period and 75.6% for Hoysala period is achieved.
