Paper Info
Title
Character Region Detection Using Structure Of Hangul Vowel Graphemes From Mobile Image
Abstract
Recently. many researchers have been proposed utilizing mobile images, whereupon the various smartphone applications have been developed on the basis of images. These applications have analyzed the images and mined the information, so they can let people search without typing keywords on the web. However, most of conventional methods for character region detection are based on clustering technique without using structural feature of character. Therefore, if a character in mobile image has complex backgrounds, these methods are difficult to localize the character region. We proposes the method to detect the Hangul character region from mobile image using structure of Hangul vowel graphemes and Hangul character type decision algorithm. First, we transform a mobile image to a gray-scale image. Second. feature extraction performed with edge and connected component based method, Edge-based method use a Canny-edge detector and connected component based method applied the local range filtering. Next, if features are not corresponding to the heuristic rule of Hangul character, extracted features filtered out and select candidates of character region. Next, candidates of Hangul character region are merged into one Hangul character using Hangul character merging algorithm. Finally, we detect the final character region by Hangul character type decision algorithm. Experimental result, proposed method could detect a character region effectively in images that contains a complex background and various environments. As a result of the performance evaluation, the recall rate is 82.33% and the proposed method showed the advanced results about detection of Hangul character region in mobile image.
Year
DOI
Venue
2011
10.1007/978-3-642-27180-9_28
GRID AND DISTRIBUTED COMPUTING
Keywords
Field
DocType
Character Region, Detection, Hangul Vowel Grapheme Structure
Heuristic,Pattern recognition,Computer science,Filter (signal processing),Speech recognition,Feature extraction,Connected component,Artificial intelligence,Vowel,Cluster analysis,Hangul,Detector
Conference
Volume
ISSN
Citations 
261
1865-0929
0
PageRank 
References 
Authors
0.34
4
3
Name
Order
Citations
PageRank
Jong-Cheon Park101.01
Byoung-Min Jun2131.56
Myoung-Kwan Oh301.01