Offline Handwritten Chinese Character Recognition viaRadical Extraction and Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Offline handwritten Chinese character recognition by radical decomposition
ACM Transactions on Asian Language Information Processing (TALIP)
Automatic Generation of Artistic Chinese Calligraphy
IEEE Intelligent Systems
Segmentation of Connected Chinese Characters Based on Genetic Algorithm
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Genetic approaches for topological active nets optimization
Pattern Recognition
Recursive hierarchical radical extraction for handwritten Chinese characters
Pattern Recognition
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Easy generation of personal Chinese handwritten fonts
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Hi-index | 0.00 |
Effective radical segmentation of handwritten Chinese characters can greatly facilitate the subsequent character processing tasks, such as Chinese handwriting recognition/identification and the generation of Chinese handwritten fonts. In this paper, a popular snake model is enhanced by considering the guided image force and optimized by Genetic Algorithm, such that it achieves a significant improvement in terms of both accuracy and efficiency when applied to segment the radicals in handwritten Chinese characters. The proposed radical segmentation approach consists of three stages: constructing guide information, Genetic Algorithm optimization and post-embellishment. Testing results show that the proposed approach can effectively decompose radicals with overlaps and connections from handwritten Chinese characters with various layout structures. The segmentation accuracy reaches 94.91% for complicated samples with overlapped and connected radicals and the segmentation speed is 0.05 second per character. For demonstrating the advantages of the approach, radicals extracted from the user input samples are reused to construct personal Chinese handwritten font library. Experiments show that the constructed characters well maintain the handwriting style of the user and have good enough performance. In this way, the user only needs to write a small number of samples for obtaining his/her own handwritten font library. This method greatly reduces the cost of existing solutions and makes it much easier for people to use computers to write letters/e-mails, diaries/blogs, even magazines/books in their own handwriting.