Localization Algorithm Based on Corner Density Detection for Overlapping Mushroom Image
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In automatic mushroom picking process, some influencing factors such as the presence of various backgrounds in the image, the huge scale difference among different mushrooms especially in overlapping mushrooms, make it tough to locate mushroom. In order to improve the target location accuracy, a new method of complex background suppression based on Harris corner detection was put forward. In view of the scale differences among overlapping mushrooms, an iterative algorithm for seeking extreme points of distance map was proposed. These extreme points were used as seeds in the Watershed algorithm for the segmentation of overlapping mushrooms. Finally, the segmented image for each overlapping mushroom was processed with the method of elliptical fitting to get the contours and center coordinate of individual mushroom. In order to verify the algorithms proposed in this study, an experiment was conducted over the mushrooms grown in the lab. The test results reveal that the location detection success rate is 86.3%. The average image processing time is 0.711 s that is aligned with the requirement of the automatic mushroom picking system.

    Reference
    Related
    Cited by
Get Citation

杨永强,叶明,陆永华,任守纲.角点密度特征下的粘连蘑菇定位算法.计算机系统应用,2018,27(5):119-125

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:August 21,2017
  • Revised:September 06,2017
  • Adopted:
  • Online: April 23,2018
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063