A Comparative Between Corner-Detectors ( Harris, Shi-Tomasi & FAST ) in Images Noisy Using Non-Local Means Filter

  • Kadhim H
  • Araheemah W
N/ACitations
Citations of this article
27Readers
Mendeley users who have this article in their library.

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

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free