A real-time image detection method applied in image matching process to assist the endovascular prothesis positioning

2004 ◽  
Vol 1268 ◽  
pp. 1249
Author(s):  
Y. Lahfi ◽  
J. Lemoine ◽  
F. Boudghene
Keyword(s):  
Real Time ◽  
Image Matching ◽  
Detection Method ◽  
Image Detection ◽  
Matching Process ◽  
Real Time Image ◽  
Time Image

scholarly journals Real-Time Image Stabilization Method Based on Optical Flow and Binary Point Feature Matching

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 198 ◽  
Author(s):  
Zilong Deng ◽  
Dongxiao Yang ◽  
Xiaohu Zhang ◽  
Yuguang Dong ◽  
Chengbo Liu ◽  
...  
Keyword(s):  
Optical Flow ◽  
Real Time ◽  
Image Matching ◽  
Image Guidance ◽  
Feature Matching ◽  
Guidance System ◽  
Stabilization Method ◽  
Image Stabilization ◽  
Real Time Image ◽  
Time Image

The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time image stabilization technology is needed to help improve the image quality of the image guidance system. To satisfy the real-time and accuracy requirements of image stabilization in the strap-down missile-borne image guidance system, an image stabilization method based on optical flow and image matching with binary feature descriptors is proposed. The global motion of consecutive frames is estimated by the pyramid Lucas-Kanade (LK) optical flow algorithm, and the interval frames image matching based on fast retina keypoint (FREAK) algorithm is used to reduce the cumulative trajectory error. A Kalman filter is designed to smooth the trajectory, which is conducive to fitting to the main motion of the guidance system. Simulations have been carried out, and the results show that the proposed algorithm improves the accuracy and real-time performance simultaneously compared to the state-of-art algorithms.

A FPGA-based architecture for real-time image matching

2013 ◽  
Author(s):  
Jianhui Wang ◽  
Sheng Zhong ◽  
Wenhui Xu ◽  
Weijun Zhang ◽  
Zhiguo Cao
Keyword(s):  
Real Time ◽  
Image Matching ◽  
Real Time Image ◽  
Time Image

A Real-Time Image Matching Algorithm for Binocular Stereo Measurement System

2019 ◽  
Author(s):  
Jianyu Duan ◽  
Lingyu Sun ◽  
Lijun Li ◽  
Zongmiao Dai ◽  
Zhenkai Xiong ◽  
...  
Keyword(s):  
Real Time ◽  
Measurement System ◽  
Image Matching ◽  
Great Influence ◽  
Consensus Method ◽  
Feature Descriptor ◽  
Matching Algorithm ◽  
Real Time Image ◽  
Binocular Stereo ◽  
Time Image

Abstract Binocular stereo measurement system can obtain accurate three-dimensional information from two-dimensional images. It has been widely applied in many fields such as vehicle tracking, robot navigating, automatic crane lifting, as well as other fields. The crucial step of binocular stereo measurement is image matching. For the image matching, it is a great challenge to ensure both real-time and matching accuracy simultaneously. The image matching algorithm has a great influence on the image matching time and accuracy. In this paper, a real-time image matching algorithm for binocular stereo measurement system is proposed based on Speedup Robust Features (SURF) algorithm. In the proposed algorithm, firstly, the key feature points are identified by the original SURF algorithm method. Secondly, the main direction of the key feature point is determined by intensity centroid method. Then, the feature descriptor is calculated by the BRIEF binary method so that the time of feature description can be shortened. Finally, RANSAC (Random Sample Consensus) method is adopted to remove mismatching points. The experiments results show that the proposed algorithm can shorten image matching time obviously and improve the accuracy of matching points.

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