A Comparison between Harris and FAST - Corner Detection of Noisy Images Using Adaptive Non-Local Means

Abstract

In this paper a comparison between Harris and FAST (Features from Accelerated Segment Test) corner detection has been presented that is track features within a noisy images where it is a challenging task in the field of image processing. As long as noisy image does not give the desired results in corner detection, de-noising is required. Adaptive non-local means are applied for salt and pepper, Gaussian and speckle noise before applying corner detection. FAST corner detection outperformed Harris in detecting actual and exact number of corners and more robust to noise than Harris, the obtained results shown a good satisfaction in this study especially in the numbers of real detected corners.