An evaluation of feature extraction algorithms for automatic language transcription system for ancient handwriting Javanese manuscripts
In order to preserve and extract the implicit knowledge of ancient Javanese manuscript, a system is required to scan and translate these manuscripts. The problem faced is the fact that most of these manuscripts are written over a very brittle medium. The best way to solve the problem is by digitalizing them to digital images, then being processed to extract the content. Optical Character Recognition is an effort to extract the content of such invaluable documents that will be followed by language translation process. Optical Character Recognition System consists of preprocessing, feature extraction, character recognition and post processing. Feature extraction works to extract distinctive features of the character that will be fed to the next step: character recognition. In this study, we evaluated several feature extraction algorithms including Local Line Direction, mesh and other different approaches in term of classification rate obtained by Support Vector Machine (SVM).
B00523 | (wh) | Available but not for loan - Missing |
No other version available