计算机工程与科学2018，Vol.40Issue(2)：292-297,6.DOI:10.3969/j.issn.1007-130X.2018.02.014
改进的SURF算法在书法笔画匹配识别中的应用
An improved SURF algorithm for calligraphy strokes recognition
摘要
Abstract
Calligraphy strokes have rich writer charateristics.Whether feature vectors can be correctly extracted and matched directly affect the recognition effect.Aiming at the problem that the traditional SURF(Scale Invariant Feature Transform)algorithm has fewer detected feature points and higher false matching rate,a SURF based on Contourlet transform is proposed.The algorithm uses Contourlet transform to do sub-band decomposition and directional filtering of calligraphic strokes before the feature points are extracted,and then obtains the low frequency and high frequency detail components.The minimum Euclidean distance criterion (LEDC) is adopted to calculate the similarity of the low-frequency detail components.After the high frequency detail components are further decomposed,the appropriate thresholds are selected to extract the high frequency feature points.Then,the SURF feature points are matched.The RANSAC algorithm is used to eliminate the false matching points.Experiments show that the improved SURF algorithm can not only extract the feature points of the strokes better,but also improve the anti-noise performance.The recognition rate is improved by 3％.关键词
SURF算法/子带分解/方向性滤波/特征点匹配Key words
SURF algorithm/subband decomposition/directional filter/feature point matching分类
信息技术与安全科学引用本文复制引用
王民,庞爽爽,周军妮..改进的SURF算法在书法笔画匹配识别中的应用[J].计算机工程与科学,2018,40(2):292-297,6.基金项目
陕西省教育厅专项基金(2013JK1081) （2013JK1081）
陕西省科学技术研究发展计划(CXY1122(2)) （CXY1122(2）
陕西省自然科学基金(2013JQ8003) （2013JQ8003）
陕西省教育厅科研计划(12JK1007) （12JK1007）
