Subpixel edge estimation using geometrical edge models with noise miniaturization

Author

Hung, D. C Douglas ; Mitchell, O.R.

Author_Institution

Dept. of Comput. Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA

fYear

1994

fDate

21-24 Apr 1994

Firstpage

112

Lastpage

117

Abstract

The significant disadvantage for traditional contour representation is as the resolution is reduced the effort of undersampling is proportional enlarged. The goal of this study is to improve edge detection results, especially for those corner points in low resolution. This study describes a method, which is based on 4-connected pixel-wise linearization, for finding contours from low resolution video images. This allows a more accurate inspection and identification of objects from image data. In practice, geometrical models are used to manipulate this linearization. A method is employed for examining the corner points as well

Keywords

edge detection; inspection; noise; 4-connected pixel-wise linearization; contour representation; corner points; geometrical edge models; image data; image orientation; low resolution video images; noise miniaturization; object identification; object inspection; subpixel edge estimation; undersampling; Brightness; Computer vision; Image edge detection; Image resolution; Information science; Inspection; Laboratories; Object recognition; Pixel; Solid modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Interpretation, 1994., Proceedings of the IEEE Southwest Symposium on

Conference_Location

Dallas, TX

Print_ISBN

0-8186-6250-6

Type

conf

DOI

10.1109/IAI.1994.336673

Filename

336673