Author(s)

Sharofiddin Allaberdiev^1*, Shokhrukh Yakhyoev², Rakhmatilla Fatkhullayev³, Jia Chen¹

¹Department of Mathematics and Computer Science, Wuhan Textile University, Wuhan, China.
²Department of Machine Science and Service, Tashkent Institute of Textile and Light Industry, Tashkent, Uzbekistan.
³Department of Information & Communication Engineering, Huazhong University of Science and Technology, Wuhan, China.

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.

Image Matching, SURF Algorithm, Features of an Image, RANSAC Algorithm

Allaberdiev, S. , Yakhyoev, S. , Fatkhullayev, R. and Chen, J. (2019) Speeded-Up Robust Feature Matching Algorithm Based on Image Improvement Technology. Journal of Computer and Communications, 7, 1-10. doi: 10.4236/jcc.2019.712001.