An Auto-adaptive Threshold Pre-detection SUSAN Corner Detection Algorithm

Author

Liangyu He ; Xingyu Zhou

Author_Institution

Sch. of Inf. Sci. & Eng., Southeast Univ., Nanjing, China

Volume

2

fYear

2013

fDate

26-27 Aug. 2013

Firstpage

511

Lastpage

514

Abstract

Corner is a significant geometrical characteristic in digital image processing. The accuracy in corner detection has much meaning in image processing and measurement. This article aims to propose an improved threshold determination method for the Smallest Univalue Segment Assimilating Nucleus corner detection algorism. This improved algorism calculates the threshold values separately for each pixel to make corner detection even under different contrast gradients perform normally. Based on the classical SUSAN algorism, corner pre-detection is used to eliminate pseudo corners and reduce calculation amount and thus improve the algorism speed. Realistic experiments prove this method practical.

Keywords

edge detection; image segmentation; Smallest Univalue Segment Assimilating Nucleus corner detection algorithm; autoadaptive threshold predetection SUSAN corner detection algorithm; contrast gradients; digital image processing; geometrical characteristic; image pixel; pseudocorner elimination; threshold determination method; threshold values; Brightness; Educational institutions; Gray-scale; Image edge detection; Noise; Shape; Autoadaptive Threshold; Corner Detection; Prediction; SUSAN Algorism;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-0-7695-5011-4

Type

conf

DOI

10.1109/IHMSC.2013.269

Filename

6642797