Memory-based recognition of camera-captured characters

This paper addresses how to quickly recognize a character pattern using a lot of case examples without learning. Here without learning means just finding the most similar example from the case examples, and pretend as if the OCR understands the definition of the character. This strategy is expected to work well in most cases with a large dataset, however, also expected to take a lot of time for finding the most similar example. In this paper, we show that a lot of case examples can be processed in a short time. As a testbed, we handle recognition problem of camera-captured printed characters. Using a database storing 100 fonts, the proposed method achieved 97.0% of recognition rate for images captured from the right angle and 95.8% for those from 45 deg. with 4.56ms of processing time, that is about 220 characters per second including every process. Categories and Subject Descriptors I.7.5 [DOCUMENT AND TEXT PROCESSING]: Document Capture—Optical character recognition (OCR); H.2.8...

• Type: Conference
• Year: 2010
• Where: DAS
• Authors: Masakazu Iwamura, Tomohiko Tsuji, Koichi Kise
• Keywords: Camera-captured Printed Characters, Case Examples, DAS 2010, Document Analysis, Similar Example