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Chinese Calligraphy Word Spotting Using Elastic HOG Feature and Derivative Dynamic Time Warping
| Content Provider | Semantic Scholar |
|---|---|
| Author | Yong Zhi-Bo Yang Kuanquan Wang |
| Copyright Year | 2014 |
| Abstract | Chinese calligraphy is a very special style of handwriting and direct character recognition is very difficult. Content-based keyword spotting is more feasible than recognition-based retrieval for calligraphy document. In this paper,we propose a novel Elastic Histogram of Oriented Gradient( EHOG) descriptor for calligraphy word spotting. The presented feature is a modification of Histogram of Oriented Gradient( HOG), widely used in human detection. In our approach,the input word image is partitioned into non-uniform rectangular cells according to the calligraphy character pixel intensity,and then in each cell a histogram of orientation is accumulated dynamically. Moreover,we adopt Derivative Dynamic Time Warping( DDTW) for image feature matching,which achieves good performance in gesture recognition. Experiments demonstrate a very significant improvement when comparing our proposed feature with previously developed ones,and also show DDTW produces superior alignments between two calligraphy character feature series than DTW. |
| Starting Page | 21 |
| Ending Page | 27 |
| Page Count | 7 |
| File Format | PDF HTM / HTML |
| Volume Number | 21 |
| Alternate Webpage(s) | https://www3.cs.stonybrook.edu/~zhibyang/papers/Calligraphy_Word_Spotting.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
