A SKYSCRAPER MOSAIC ALGORITHM BASED ON SIFT

Authors

  • Bhagyashri R. Pandurangi Electronics and communication Gogte Institute of TechnologyBelgaum, India
  • Keshav Y. Patil Electronics and communication Gogte Institute of TechnologyBelgaum, India

Keywords:

EXISTING SYSTEM, PERFORMANCE ASSESSMENT PARAMETERS

Abstract

This project concerns the problem of standing skyscraper image mosaic based on SIFT. In standing skyscraper calculation based on image enhancement or image processing, the first aim is to take picture of the deliberate tall building. Due to some special tall building, or incomplete by geographical conditions, it is impossible to capture complete image of the tall building at one time, and need to shoot sequence tall building images with overlapped areas and stitch them. Here a building picture mosaic method based on SIFT (Scale Invariant Feature Transform) was put ahead. Firstly, the SIFT characteristic vector of every picture was calculated and the feature points are matched using SIFT features. Then the standpoint transform was carried out to the image which was attached by selected four pixels. Finally, the sequence images are stitched based on weighted feature. The experiment of true building image sequence stitching achieves the enhanced flat mosaic effect and show this technique is successful.

Downloads

Published

2021-03-27

Issue

2015: ICITDCEME

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format
  2. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. NonCommercial — You may not use the material for commercial purposes .
  3. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
  4. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

 

Rights of Authors

Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.