Data Fusion of Radar Image and ECDIS Based on Matching of Harris Feature Points

2011 ◽  
Vol 317-319 ◽  
pp. 2026-2029 ◽  
Author(s):  
Chuang Zhang ◽  
Zhong Zhou Fan
Keyword(s):  
Image Registration ◽  
Image Fusion ◽  
Wavelet Transformation ◽  
Transformation Method ◽  
Image Features ◽  
Image Feature ◽  
Feature Points ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Electronic Chart

This paper analyzes automatic image registration algorithm, and image features of radar and electronic chart, then, image registration algorithm based on Harris feature point are given, in which the methods are specially described. Wavelet transformation method on image feature should be considered. Moreover, simulate results of image fusion.

A New Algorithm of Image Registration Based on Contour Feature

2014 ◽  
Vol 912-914 ◽  
pp. 1092-1097
Author(s):  
Fu Hua Song ◽  
Peng Hui Li ◽  
Jian Ran Deng
Keyword(s):  
Image Registration ◽  
Rotation Angle ◽  
Closed Contour ◽  
Feature Points ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Contour Feature ◽  
Circular Correlation ◽  
Open Contour ◽  
Calculated Amount

Image registration is an important task in image processing. In this paper, a new and fast contour-based image registration algorithm is proposed. In this algorithm, we fetch contour points and calculate the normal angles firstly, then figure out the histogram of the contour-feature points. By computing circular correlation of the histogram, the rotation angle can be gained. As the rotation angle is obtained, it vastly simplifies the complexity of estimating other registration parameters and reduces the calculated amount, thus achieving a fast image registration algorithm. This algorithm has the invariance of rotation, translation and scale, and it has high robustness for either open contour or closed contour.

A Robust Image Registration Algorithm Based on Feature Points Matching

2008 ◽  
Vol 28 (3) ◽  
pp. 454-461 ◽  
Author(s):  
刘贵喜 Liu Guixi ◽  
刘冬梅 Liu Dongmei ◽  
刘凤鹏 Liu Fengpeng ◽  
周亚平 Zhou Yaping
Keyword(s):  
Image Registration ◽  
Feature Points ◽  
Registration Algorithm ◽  
Feature Points Matching ◽  
Image Registration Algorithm ◽  
Robust Image

A New Fast Multi-Source Remote Sensing Image Registration Algorithm

2012 ◽  
Vol 452-453 ◽  
pp. 950-953
Author(s):  
Yong Mei Zhang ◽  
Li Ma
Keyword(s):  
Remote Sensing ◽  
Image Registration ◽  
Control Point ◽  
Feature Points ◽  
Remote Sensing Images ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Shift Rotation ◽  
Back Ground

Aiming at the registration of multi-sensor remote sensing images, a fast and effective image registration algorithm method is presented. In this algorithm, using SIFT to extract feature points, remove mismatching points through Delaunay triangulation, and introduce distance calculation into the determination of homologous control point pairs. The effect of image registration algorithm is evaluated by subjective and objective method. Experiment results show the proposed algorithm can accurately register multi-spectral and panchromatic images with some shift, rotation angles and back-ground noises, and it can inrease the speed and precision of registration.

scholarly journals Feature Point Registration Model of Farmland Surface and Its Application Based on a Monocular Camera

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3799
Author(s):  
Yang Li ◽  
Dongyan Huang ◽  
Jiangtao Qi ◽  
Sikai Chen ◽  
Huibin Sun ◽  
...  
Keyword(s):  
Image Registration ◽  
Field Test ◽  
Feature Detection ◽  
Roll Angle ◽  
Image Feature ◽  
Speeded Up Robust Features ◽  
Registration Algorithm ◽  
Agricultural Equipment ◽  
Monocular Camera ◽  
Image Registration Algorithm

In this study, an image registration algorithm was applied to calculate the rotation angle of objects when matching images. Some commonly used image feature detection algorithms such as features from accelerated segment test (FAST), speeded up robust features (SURF) and maximally stable extremal regions (MSER) algorithms were chosen as feature extraction components. Comparing the running time and accuracy, the image registration algorithm based on SURF has better performance than the other algorithms. Accurately obtaining the roll angle is one of the key technologies to improve the positioning accuracy and operation quality of agricultural equipment. To acquire the roll angle of agriculture machinery, a roll angle acquisition model based on the image registration algorithm was built. Then, the performance of the model with a monocular camera was tested in the field. The field test showed that the average error of the rolling angle was 0.61°, while the minimum error was 0.08°. The field test indicated that the model could accurately obtain the attitude change trend of agricultural machinery when it was working in irregular farmlands. The model described in this paper could provide a foundation for agricultural equipment navigation and autonomous driving.

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