Title :
A segmentation-free approach to OCR
Author :
Chen, C.H. ; DeCurtins, J.L.
Author_Institution :
Inf., Telecommun. & Autom. Div., SRI Int., Menlo Park, CA, USA
fDate :
30 Nov-2 Dec 1992
Abstract :
When confronted with degraded images of text, however, the performance of many commercial OCR systems deteriorates severely. This occurs because all these systems rely on a segmentation step that is prone to error in the presence of image noise and printing artifacts. The authors present a novel OCR approach that overcomes this problem by eliminating the segmentation step altogether. This approach is based on the concept and techniques of occluded object recognition. To achieve high efficiency as well as robustness, they incorporate the notions of indexing and voting, and tailor them to the problem of OCR. Preliminary experimental results are given
Keywords :
feature extraction; image recognition; optical character recognition; degraded images; feature extraction; image noise; indexing; occluded object recognition; optical character recognition; pose clustering; printing artifacts; robustness; voting; Application software; Character recognition; Computer vision; Degradation; Image segmentation; Object recognition; Optical character recognition software; Printing; Text analysis; Voting;
Conference_Titel :
Applications of Computer Vision, Proceedings, 1992., IEEE Workshop on
Conference_Location :
Palm Springs, CA
Print_ISBN :
0-8186-2840-5
DOI :
10.1109/ACV.1992.240312