Chinese Calligraphy Word Spotting Using Elastic HOG Feature and Derivative Dynamic Time Warping
Chinese Calligraphy Word Spotting Using Elastic HOG Feature and Derivative Dynamic Time
Warping
Yong Xia,Zhi-Bo Yang,Kuan-Quan Wang
【摘 要】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. 【期刊名称】哈尔滨工业大学学报(英文版) 【年(卷),期】2014(000)002