Title :
Skeletonization for fuzzy degraded character images
Author :
Chen, Shy-Shyan ; Shih, Frank Y.
Author_Institution :
Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA
fDate :
10/1/1996 12:00:00 AM
Abstract :
Most skeletonization algorithms are operated on binary images. To avoid information loss and distortion, a topography-based approach is proposed to apply directly on fuzzy or gray scale images. A membership function is used to indicate the degree of membership of each ridge point with respect to the skeleton. Significant ridge points are linked to form strokes of skeleton. Experimental results show that our algorithm can reduce deformation of junction points anti correctly extract the whole skeleton, although a character may be broken into pieces. For merged characters, the breaking positions can be located by searching for the saddle points. A multiple context confirmation is used to increase the reliability of breaking hypotheses
Keywords :
character recognition; edge detection; image classification; binary images; breaking hypotheses reliability; breaking positions; experimental results; fuzzy degraded character images; gray scale images; information distortion; information loss; membership function; merged characters; multiple context confirmation; ridge points; saddle points; skeletonization algorithms; topography based approach; unsupervised character classification; Algorithm design and analysis; Brightness; Computer vision; Degradation; Fuzzy sets; Gray-scale; Pixel; Prototypes; Skeleton; Surface topography;
Journal_Title :
Image Processing, IEEE Transactions on