Leaf area measurement based on Markov random field

Author

Dianyuan Han

Author_Institution

Dept. of Comput. Eng., Wei Fang Univ., Weifang, China

fYear

2012

fDate

29-31 Dec. 2012

Firstpage

1745

Lastpage

1749

Abstract

This paper concerns the plant leaf area measurement based on improved image processing. Firstly, the referenced rectangle was detected with 2-side scan method. Then the leaf region was segmented according to 2G-R-B of every pixel with two thresholds, and by using of dilatation operation, the trimap of leaf image was got. Next the pixels in unknown area were classified to the foreground or background area with improved knockout method and the exact leaf was segmented. Lastly, the leaf area was calculated according to the pixels proportion between leaf region and the referenced rectangle. Experiment results show our methods have good accuracy and rapid speed.

Keywords

Markov processes; biology computing; botany; image classification; image segmentation; object detection; random processes; 2-side scan method; 2G-R-B; Markov random field; area classification; background area; dilatation operation; foreground area; image processing; improved knockout method; leaf image trimap; leaf region segmentation; plant leaf area measurement; referenced rectangle detection; MRF; image processing; image segmentation; leaf area measurement; natural image matting;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on

Conference_Location

Changchun

Print_ISBN

978-1-4673-2963-7

Type

conf

DOI

10.1109/ICCSNT.2012.6526258

Filename

6526258