Photo time-stamp detection and recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Photo Time-Stamp Recognition Based on Particle Swarm Optimization
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
A novel image fusion method based on SGNN
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
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Photo time-stamp is a valuable information source for content-based retrieval of scanned photo databases. A fast photo-stamp recognizing approach based on Self-Generating Neural Networks (SGNN) is proposed in this paper. Network structures and parameters of SGNN needn’t to be set by users, and their learning process needn’t iteration, so SGNN can be trained on-line. Proposed method consists of three steps: A photo is roughly segmented to determine which corner of the photo contains time-stamp; The area which contains time-stamp of the photo is finely segmented, in order to locate each character in the time-stamp, projection technology is used to locate edges of these characters; The time-stamp is recognized based on SGNN. Experimental results show that proposed approach can achieve higher recognition accuracy and computing efficiency.