Abstract
Panorama generation systems aim at creating a wide-view image by aligning and stitching a sequence of images. The technology is extensively used in many fields such as virtual reality, medical image analysis, and geological engineering. This research is concerned with combining multiple images with a region of overlap to produce a wide field of view by the detection of feature points for images with different camera motion in an efficient and fast way. Feature extraction and description are important and critical steps in panorama construction. This study presents techniques of corner detection, moment invariant and random sampling to locate the important features and built storing descriptors in the images under noise, transformation, lighting, little viewpoint changes, blurring and compression circumstances. Corner detection and normalization are used to extract features in the image, while the descriptors are built by moment invariant in an efficient way. Finally, the matching and motion estimation is implemented based on the random sampling method. The results of experiments conducted on images and video sequences taken by handheld camera and images taken from the internet. The results show that the proposed algorithm generates panoramic image and panoramic video of good quality in a fast and efficient way.
Highlights
Panoramic view construction is one of the most computer vision applications that have a great attention recently
Panoramic scene generation is an important topic because it needs a fusion of image processing, graphics and computer vision techniques
Many researchers deal with generating panoramic image depending on the Scale Invariant Feature Transform (SIFT) method but in this work, a panoramic image using a proposed feature extraction method is generated
Summary
Panoramic view construction is one of the most computer vision applications that have a great attention recently. The technology of panoramic view is developed rapidly and becomes a kind of popular visual technology, because the visual panorama technology can bring people a new real visualization of the scene and interactive experience [1][2]. It aims at creating a wide view image by aligning and stitching a sequence of images that having a significant overlap. Image Registration is the process of matching two or more images of the scene. Image registration is of great importance in all processing and analysis tasks based on the combination of data from sets of images. Image registration algorithms can be divided into two major categories: feature-based methods and area-based methods
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
