Implementation of Speeded Up Robust Feature Algorithm for Real Time Logo Detection

Authors

  • Amarja Indapwar  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India
  • Hemangi Oke  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India
  • Madhura Chikte  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India
  • Poonam Barai  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India
  • Pratima Katre  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India
  • Prof Nirmal Mungale  Computer Science Department, Rajiv Gandhi College of Engineering and Research, RTMNU, Hingna Road, Wanadongri, Nagpur, India

Keywords:

Logo detection, OpenCV, SURF, logo extraction, recognition, Visual Data

Abstract

Logo detection in unconstrained pictures is testing, especially when just exceptionally inadequate marked preparing pictures are open because of high naming expenses. In this work, we depict a model preparing picture blending strategy equipped for enhancing essentially logo detection execution when just a modest bunch of named preparing pictures caught in reasonable setting are accessible, evading broad manual marking costs. In particular, the framework gives detail data in regards to the area of logo in the live video and pictures. This procedure is completed by utilizing Speeded Up Robust Feature (SURF) algorithm. It reveals either uncalled for or unapproved utilization of logos. Reference logos and test pictures are changed over into twofold shape and their features are coordinated in like manner. The primary point of this venture is to show an effective and robust armature to find and also perceive logo pictures using Computer Vision (OpenCV). The restriction and acknowledgment of logos from live video is a major test that has been embraced in this examination. For benchmarking model execution, we present another logo detection dataset TopLogo-10 gathered from top 10 most famous apparel/wearable brand name logos caught in rich visual setting. Broad comparisons demonstrate the benefits of our proposed SCL display over the best in class options for logo detection utilizing two genuine logo benchmark datasets: FlickrLogo-32.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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

How to Cite

[1]
Amarja Indapwar, Hemangi Oke, Madhura Chikte, Poonam Barai, Pratima Katre, Prof Nirmal Mungale, " Implementation of Speeded Up Robust Feature Algorithm for Real Time Logo Detection, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1024-1030, January-February-2018.