Edge feature extraction based on digital image processing techniques

Edge detection is a basic and important subject in computer vision and image processing. In this paper we discuss several digital image processing techniques applied in edge feature extraction. Firstly, wavelet transform is used to remove noises from the image collected. Secondly, some edge detection operators such as Differential edge detection, Log edge detection, Canny edge detection and Binary morphology are analyzed. And then according to the simulation results, the advantages and disadvantages of these edge detection operators are compared. It is shown that the Binary morphology operator can obtain better edge feature. Finally, in order to gain clear and integral image profile, the method of bordering closed is given. After experimentation, edge detection method proposed in this paper is feasible.

[1]  J. Canny A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Wang Guo-qiang Wavelet Analysis and Its Application in Image Manipulation , 2001 .

[3]  He Xi-ping Image processing and analysis based on MATLAB , 2003 .

[4]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[5]  Jong-Hwan Kim,et al.  A two-step circle detection algorithm from the intersecting chords , 2001, Pattern Recognit. Lett..