Research on the Edge Detection Method of the Rice Leaves Image Based on Phase Consistency under the Complex Environment

Article Preview

Abstract:

In order to realize the effective segmentation of the rice leaf lesion, how to remove background interference and isolating single rice leaf from collected images is the basis of disease classification and recognition. The main body information of the images collected under the simple background of lighting box and field contains only single leaf, so we can use the normal way to detect the blade edge. However, because of the outside interference under the background of field, parameters can't be quantified and the treatment effect of using ordinary edge detection methods is bad. This paper takes advantage of the characteristics that phase consistency test methods that protect them from the image contrast and brightness change and have a strong ability to resist noise to realize complete extraction of the main blade edge in the rice leaf image under the complex background.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 605-607)

Pages:

2145-2148

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Gan Jinlai, Liu Zhao, the image feature detection algorithm based on phase[J]. Experimental Science and Technology, 2006 (2) : 16-19.

Google Scholar

[2] MCMorrone & RAOwens. Feature detection from local Eenergy [J]. Pattern Recognition Letters, 1987, 6 (5): 303-313.

Google Scholar

[3] Yuan Haidong. Research of low-level visual features detection technology based on the gradient and phase information[D]. Beijing: Beijing University of Posts and Telecommunications, (2008).

Google Scholar

[4] Xiao Z T, HOU ZX. Phase based feature detector consistent with human visual system characteristics [J]. Pattern RecognitionLetters, 2004, 25 (10): 1 115-1 121.

DOI: 10.1016/j.patrec.2004.03.018

Google Scholar

[5] XIAO Z T, HOU ZX, MIAOCY, etal. Using phase information for symmetry detection [J]. Pattern Recognition Letters, 2005, 26 (13): 1985-(1994).

DOI: 10.1016/j.patrec.2005.02.003

Google Scholar

[6] Venkatesh S. & Owens RA. An energy feature detection seheme [C]. In The Intemational Conferenee on Image Proeessing, Singapore, 1989, 553-557.

Google Scholar

[7] Weng Xiumei. Image segmentation study through Phase information [J]. Tianjin: Tianjin University of Technology, (2008).

Google Scholar

[8] Luo Bin, Tu Zhengzheng, Guo Yutang. Moving target Extraction based on motion information and the phase coherence [J]. Journal of system simulation, 2008, 20 (1): 94-98.

Google Scholar