Enhanced Image Retrieval using Hybrid ORB Algorithm

Authors

  • Manish Kumar Thakur, Raju Ramakrishna Gondkar

Keywords:

Canny Edge, Computer Vision, Feature Detection, Feature Matching, Hybrid ORB, Image Processing, Mean Blur, ORB, Performance Evaluation, SIFT

Abstract

Achieving precise feature matching is a critical challenge in the field of computer vision, with applications ranging from image stitching and 3D reconstruction to image retrieval. This research paper presents an in-depth comparative analysis of the Hybrid ORB algorithm in conjunction with the widely recognized basic ORB and SIFT algorithm for image feature matching. The study meticulously evaluates the performance of these algorithms, encompassing aspects of accuracy, speed, and robustness, under various rotation and scaling scenarios. Furthermore, the research explores the distinct advantages of Hybrid ORB, an amalgamation of Canny Edge and Mean blur techniques, which enhances feature detection and matching. This work sheds light on the essential roles that these algorithms play in modern computer vision applications and lays the groundwork for future innovations in advanced image retrieval.

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References

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ISSN: 2582-4104.

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Published

12.06.2024

How to Cite

Manish Kumar Thakur. (2024). Enhanced Image Retrieval using Hybrid ORB Algorithm. International Journal of Intelligent Systems and Applications in Engineering, 12(4), 4833–4839. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7190

Issue

Vol. 12 No. 4 (2024)

Section

Research Article

License

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