Real-time multi-beam SEM image stitching (Conference Presentation)

2018 ◽  
Author(s):  
Shammi Rahangdale ◽  
Lennard Voortman ◽  
Pieter Kruit
Keyword(s):  
Real Time ◽  
Image Stitching ◽  
Sem Image

Real Time Panoramic Video in OpenCV using Image Stitching Techniques

2018 ◽  
Vol 06 (03) ◽  
pp. 184-187
Author(s):  
K. Rajasri ◽  
D. Gayathri ◽  
Balasundari Ilanthirayan ◽  
A. Sundra
Keyword(s):  
Real Time ◽  
Image Stitching ◽  
Panoramic Video ◽  
Stitching Techniques

Real-Time Panorama and Image Stitching with Surf-Sift Features

2021 ◽  
Author(s):  
Sheshang Degadwala ◽  
Utsho Chakraborty ◽  
Promise Kuri ◽  
Haimanti Biswas ◽  
Ahmed Nur Ali ◽  
...  
Keyword(s):  
Real Time ◽  
Image Stitching ◽  
Sift Features

scholarly journals Fixed Homography-Based Real-Time SW/HW Image Stitching Engine for Motor Vehicles

ETRI Journal ◽  
2015 ◽  
Vol 37 (6) ◽  
pp. 1143-1153 ◽  
Author(s):  
Jung-Hee Suk ◽  
Chun-Gi Lyuh ◽  
Sanghoon Yoon ◽  
Tae Moon Roh
Keyword(s):  
Real Time ◽  
Motor Vehicles ◽  
Image Stitching

scholarly journals Real-time and automatic map stitching through aerial images from UAV

2021 ◽  
Vol 2120 (1) ◽  
pp. 012025
Author(s):  
J N Goh ◽  
S K Phang ◽  
W J Chew
Keyword(s):  
Real Time ◽  
Matrix Multiplication ◽  
Image Features ◽  
Aerial Images ◽  
Aerial Image ◽  
Process Time ◽  
Image Stitching ◽  
Singular Value Decomposition Method ◽  
Value Decomposition ◽  
Computational Resources

Abstract Real-time aerial map stitching through aerial images had been done through many different methods. One of the popular methods was a features-based algorithm to detect features and to match the features of two and more images to produce a map. There are several feature-based methods such as ORB, SIFT, SURF, KAZE, AKAZE and BRISK. These methods detect features and compute homography matrix from matched features to stitch images. The aim for this project is to further optimize the existing image stitching algorithm such that it will be possible to run in real-time as the UAV capture images while airborne. First, we propose to use a matrix multiplication method to replace a singular value decomposition method in the RANSAC algorithm. Next, we propose to change the workflow to detect the image features to increase the map stitching rate. The proposed algorithm was implemented and tested with an online aerial image dataset which contain 100 images with the resolution of 640 × 480. We have successfully achieved the result of 1.45 Hz update rate compared to original image stitching algorithm that runs at 0.69 Hz. The improvement shown in our proposed improved algorithm are more than two folds in terms of computational resources. The method introduced in this paper was successful speed up the process time for the program to process map stitching.

scholarly journals Designing a New Endoscope for Panoramic-View with Focus-Area 3D-Vision in Minimally Invasive Surgery

2019 ◽  
Vol 40 (2) ◽  
pp. 204-219
Author(s):  
Dinh Thai Kim ◽  
Ching-Hwa Cheng ◽  
Don-Gey Liu ◽  
Kai Che Jack Liu ◽  
Wayne Shih Wei Huang
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Depth Perception ◽  
Frame Rate ◽  
Image Stitching ◽  
Panoramic View ◽  
3D Vision ◽  
3D Surface

Abstract Purpose The minimally invasive surgery (MIS) has shown advantages when compared to traditional surgery. However, there are two major challenges in the MIS technique: the limited field of view (FOV) and the lack of depth perception provided by the standard monocular endoscope. Therefore, in this study, we proposed a New Endoscope for Panoramic-View with Focus-Area 3D-Vision (3DMISPE) in order to provide surgeons with a broad view field and 3D images in the surgical area for real-time display. Method The proposed system consisted of two endoscopic cameras fixed to each other. Compared to our previous study, the proposed algorithm for the stitching videos was novel. This proposed stitching algorithm was based on the stereo vision synthesis theory. Thus, this new method can support 3D reconstruction and image stitching at the same time. Moreover, our approach employed the same functions on reconstructing 3D surface images by calculating the overlap region’s disparity and performing image stitching with the two-view images from both the cameras. Results The experimental results demonstrated that the proposed method can combine two endoscope’s FOV into one wider FOV. In addition, the part in the overlap region could also be synthesized for a 3D display to provide more information about depth and distance, with an error of about 1 mm. In the proposed system, the performance could achieve a frame rate of up to 11.3 fps on a single Intel i5-4590 CPU computer and 17.6 fps on a computer with an additional GTX1060 Nvidia GeForce GPU. Furthermore, the proposed stitching method in this study could be made 1.4 times after when compared to that in our previous report. Besides, our method also improved stitched image quality by significantly reducing the alignment errors or “ghosting” when compared to the SURF-based stitching method employed in our previous study. Conclusion The proposed system can provide a more efficient way for the doctors with a broad area of view while still providing a 3D surface image in real-time applications. Our system give promises to improve existing limitations in laparoscopic surgery such as the limited FOV and the lack of depth perception.

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