Abstract
A comparative study was conducted in this paper , between three algorithms which (Harris , Shi-Tomasi , FAST ) interested-points detection to identified the features that required to match , recognize and track objects in images noisy . Detect the interested-points in image noisy one of the most challenges in field of image processing . The noise consider the main cause for damage the natural images during the acquisition and transition , and detect the interested-points of these images doesn’t give the desired results , so eliminating noise from this images is very important , Non-local means approach is applied for solve this problem .
Cite
CITATION STYLE
Kadhim, H. A., & Araheemah, W. A. (2019). A Comparative Between Corner-Detectors ( Harris, Shi-Tomasi & FAST ) in Images Noisy Using Non-Local Means Filter. Journal of Al-Qadisiyah for Computer Science and Mathematics, 11(3). https://doi.org/10.29304/jqcm.2019.11.3.609
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