液晶与显示2016，Vol.31Issue(11)：1070-1078,9.DOI:10.3788/YJYXS20163111.1070
结合 MSER 与 HSOG 的目标局部特征提取
Target local feature extraction combined MSER and HSOG
摘要
Abstract
For the defect in describing object geometry features of SIFT at viewpoint variation,a new local feature extraction method is proposed in this paper,which combined maximally stable extremal region(MSER)and histogram of second order gradient(HSOG).First,a new most stability criterion is adopted to improve the detection effect at irregular shaped regions and under blur conditions.Then, the local feature descriptors of MSER is extracted by the improved histogram of second-order gradient;the influences of different pixels on central pixel of MESR region are considered by weighted Gaussian function method and the stability is improved.Finally,the method proposed is verified through image match with standard test images and real images.Experimental results show that the method proposed can still achieve more than 70% matching rate at different viewpoint,which is better than SIFT.Compared with the traditional method,the presented method achieves an excellent detec-tion effect for irregularly shaped areas,which is suitable for target matching when viewpoint is cur-rent.关键词
信息处理技术/MSER+HSOG/图像匹配局部特征Key words
signal process technology/MSER+HSOG/image match/local feature分类
信息技术与安全科学引用本文复制引用
郭汉洲,郭立红,吕游..结合 MSER 与 HSOG 的目标局部特征提取[J].液晶与显示,2016,31(11):1070-1078,9.基金项目
国家自然科学基金(No．61036015) Supported by National Natural Science Foundation of China(No．61036015) （No．61036015）
