Abstract
Due to requirements and necessities in digital image research, image matching is considered as a key, essential and complicating point especially for machine learning. According to its convenience and facility, the most applied algorithm for image feature point extraction and matching is Speeded-Up Robust Feature (SURF). The enhancement for scale invariant feature transform (SIFT) algorithm promotes the effectiveness of the algorithm as well as facilitates the possibility, while the application of the algorithm is being applied in a present time computer vision system. In this research work, the aim of SURF algorithm is to extract image features, and we have incorporated RANSAC algorithm to filter matching points. The images were juxtaposed and asserted experiments utilizing pertinent image improvement methods. The idea based on merging improvement technology through SURF algorithm is put forward to get better quality of feature points matching the efficiency and appropriate image improvement methods are adopted for different feature images which are compared and verified by experiments. Some results have been explained there which are the effects of lighting on the underexposed and overexposed images.
Highlights
Image matching is an important technology in image processing
The idea based on merging improvement technology through Speeded-Up Robust Feature (SURF) algorithm is put forward to get better quality of feature points matching the efficiency and appropriate image improvement methods are adopted for different feature images which are compared and verified by experiments
SURF algorithm is an improvement of the scale invariant feature transform (SIFT) algorithm
Summary
Image matching is an important technology in image processing. Point feature matching is a basic method in image matching. SURF feature matching works well when the light is good but it doesn’t match well when the light is insufficient or overexposed [6] [7]. This paper proposes the idea of combining image improvement technology with SURF algorithm by using different image improvement methods for processing in advance and through experimental verification, the SURF algorithm combined with image improvement technology improves feature extraction and matching [11] [12]
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 callDisclaimer: 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.
