Object Detection using Different Point Feature Techniques: A Comparative Analysis
Suhas Reddy P1, Bhargavi Rao B2, Jayanth Anala3, Megha Dangayach4
1Suhas Reddy P, Department of Computer Science & Engineering, Vellore Institute of Technology, Chennai (Tamil Nadu), India.
2Bhargavi Rao, Department of Computer Science & Engineering, Vellore Institute of Technology, Chennai (Tamil Nadu), India.
3Jayanth Anala, Department of Computer Science & Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
4Megha Dangayach, Department of Computer Science & Engineering, Vellore Institute of Technology, Chennai (Tamil Nadu), India.
Manuscript received on 03 October 2022 | Revised Manuscript received on 11 October 2022 | Manuscript Accepted on 15 November 2022 | Manuscript published on 30 November 2022 | PP: 1-4 | Volume-11 Issue-12, November 2022 | Retrieval Number: 100.1/ijitee.L930811111222 | DOI: 10.35940/ijitee.L9308.11111222
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Abstract: The image Recognition system is a vital problem in the field of computer vision because it must be precise, successful in the desired goal, strong, healthy, and self-loading. The following are the most critical essential phases in image alignment/registration: feature matching, feature detection, derivation of transformation function based on related features in pictures, and reconstruction of images based on generated transformation function. In many applications, the goal of computer vision is to create an ideal and accurate image, which is dependent on optimal feature matching and detection. This paper’s inquiry summarizes the similarity among five alternative approaches for robust features/interest points (or landmarks) detector and picture identification. This research also focuses on the extraction of unique features from photos that may be utilized to conduct effective matching of diverse perspectives of the images/objects/scenes.
Keywords: Affine, BRISK, Feature extraction and matching, In Lier, ORB, Rotation, Invariance, SURF, Scaleinvaraince, estimate Geometric Transform 2D
Scope of the Article: Geometric Transform