Edge detection of images based on improved Sobel operator and genetic algorithms

Author

Jin-Yu, Zhang ; Yan, Chen ; Xian-Xiang, Huang

Author_Institution

Xi´´an Res. Inst. of High-tech, Xi´´an

fYear

2009

fDate

11-12 April 2009

Firstpage

31

Lastpage

35

Abstract

Edge detection of images is a classical problem in computer vision and image processing. The key of edge detection is the choice of threshold; the choice of threshold directly determines the results of edge detection. How to automatically determine an optimal threshold is one of difficult points of edge detection. In this paper, Sobel edge detection operator and its improved algorithm are first discussed in term of optimal thresholding. Then based on genetic algorithms and improved Sobel operator, a new automatic threshold algorithm for images processing is proposed. Finally, the edge detection experiments of two real images are conducted by means of two algorithms. The comparative experiment results show that the new algorithm of automatic threshold is very effective. The results are also better than the classical Otsu methods.

Keywords

computer vision; edge detection; genetic algorithms; image segmentation; Sobel operator; automatic image threshold algorithm; computer vision; edge detection; genetic algorithm; image processing; Computer errors; Computer vision; Data mining; Genetic algorithms; Image color analysis; Image edge detection; Image generation; Image processing; Image segmentation; Image texture analysis; Classes Square Error; Edge Detection; Genetic Algorithms; Image Processing; Sobel Operator;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Signal Processing, 2009. IASP 2009. International Conference on

Conference_Location

Taizhou

Print_ISBN

978-1-4244-3987-4

Type

conf

DOI

10.1109/IASP.2009.5054605

Filename

5054605