A new edge detection algorithm based on a statistical approach

Author

Fesharaki, M.N. ; Hellestrand, Graham R.

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., New South Wales Univ., Kensington, NSW, Australia

fYear

1994

fDate

13-16 Apr 1994

Firstpage

21

Abstract

A method of generating edge maps thereby segmenting an image into regions based on the Student t-test is presented. By applying this test to compare the distribution functions of the intensities in the neighborhood of a given pixel, the pixel can be accurately classified as either an edge pixel on the boundary between regions, or as a pixel of a particular type of regions. The results show that using 5×5 window, this method robustly segments both synthetic and natural images, and maintains this performance in the presence of additive noise

Keywords

edge detection; image segmentation; random noise; statistical analysis; Gausian noise; Student t-test; additive noise; distribution functions; edge detection algorithm; edge maps generation; edge orientation; edge pixel; image intensities; image segmentation; natural images; statistical approach; synthetic images; Australia; Computer science; Gaussian noise; Image edge detection; Image segmentation; Laboratories; Laplace equations; Noise robustness; Partitioning algorithms; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on

Print_ISBN

0-7803-1865-X

Type

conf

DOI

10.1109/SIPNN.1994.344975

Filename

344975