###
DOI:
计算机系统应用英文版:2016,25(4):167-173
本文二维码信息
码上扫一扫!
高斯二阶差分特征算子在图像拼接中的应用
(1.重庆工业职业技术学院, 机械工程学院, 重庆 401120;2.重庆工业职业技术学院, 管理工程学院, 重庆 401120)
Image Mosaic Method Based on Gaussian Second-Order Difference Feature Operator
(1.Department of Mechanical Engineering, Chongqing Industry Polytechnic College, Chongqing 401120, China;2.Department of Management Engineering, Chongqing Industry Polytechnic College, Chongqing 401120, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1163次   下载 2573
Received:August 04, 2015    Revised:October 08, 2015
中文摘要: 为了将同一场景中具有重叠区域序列的图像快速准确合成一幅具有宽视角、高分辨率的图像,提出了基于高斯二阶差分(D2oG)特征检测算子的SIFT算法.采用高斯二阶差分(D2oG)金字塔的过零点检测提取图像尺度不变特征点,并选用RANSAC算法对特征点匹配对进行提纯,在此基础上计算不变换矩阵H,最后,用渐进渐出平滑算法完成图像的无缝拼接.实验中分别采用所提方法和SIFT算法对具有典型变换的4种图像进行拼接与测试,结果表明:所提方法提取的匹配点数、拼接所消耗时间明显低于采用SIFT算法,同时匹配效率也高于后者.此方法降低了运算复杂度的同时,图像拼接实时性也得到提高.
Abstract:In order to compose the wide visual angle and high resolution image from the sequence of images which have overlapping region in the same scene quickly and correctly, an improved SIFT algorithm which based on D2oG interest point detector was proposed. It extracted the image feature points and generated corresponding feature descriptors by improved SIFT algorithm. Then, feature point matching pairs were purified using the random consistency(RANSAC) algorithm and the transformation matrix H was caculated. Last, the seamless mosaic of images was completed by using the image fusion algorithm of slipping into and out. The images which had the four typical transformations were separately processed with the traditional SIFT and the proposed method in the experiment. The result indicated that the number of feature pairs is fewer, the mosaic time is shorter and the matching efficiency is higher than that of SIFT algorithm. This method reduces the complexity of operation and improves real-time of image mosaic simultaneously.
文章编号:     中图分类号:    文献标志码:
基金项目:重庆市高等学校青年骨干教师资助项目(自然科学类);重庆市工业职业技术学院科研项目自然科学基金(GZY201313)
引用文本:
徐敏,莫东鸣,张祯.高斯二阶差分特征算子在图像拼接中的应用.计算机系统应用,2016,25(4):167-173
XU Min,MO Dong-Ming,ZHANG Zhen.Image Mosaic Method Based on Gaussian Second-Order Difference Feature Operator.COMPUTER SYSTEMS APPLICATIONS,2016,25(4):167-173