An automatic counting method of maize ear grain based on image processing

Mingming Zhao, Jian Qin, Shaoming Li, Zhe Liu, Jin Cao, Xiaochuang Yao, Sijing Ye, Lin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Corn variety testing is a process to pick and cultivate a high yield, disease resistant and outstandingly adaptive variety from thousands of corn hybrid varieties. In this process, we have to do a large number of comparative tests, observation and measurement. The workload of this measurement is very huge, for the large number of varieties under test. The grain numbers of maize ear is an important parameter to the corn variety testing. At present, the grain counting is mostly done by manpower. In this way, both the deviation and workload is unacceptable. In this paper, an automatic counting method of maize ear grain is established basing on image processing. Image segmentation is the basis and classic difficult part of image processing. This paper presents an image pre-processing method, which is based on the characteristics of maize ear image. This method includes median filter to eliminate random noise, wallis filter to sharpen the image boundary and histogram enhancement. It also mainly introduces an in-depth study of Otsu algorithms. To overcome the problems of Otsu algorithm that background information being erroneously divided when object size is small. A new method based on traditional Otsu method is proposed, which combines the multi-threshold segmentation and RBGM gradient descent. The implementation of RBGM gradient descent leads to a remarkable improvement on the efficiency of multi-threshold segmentation which is generally an extremely time-consuming task. Our experimental evaluations on 25 sets of maize ear image datasets show that the proposed method can produce more competitive results on effectiveness and speed in comparison to the manpower. The grain counting accuracy of ear volume can reach to 96.8%.

Original languageEnglish (US)
Title of host publicationComputer and Computing Technologies in Agriculture - 8th IFIPWG 5.14 International Conference, CCTA 2014, Revised Selected Papers
PublisherSpringer New York LLC
Pages521-533
Number of pages13
ISBN (Print)9783319196190
DOIs
StatePublished - Jan 1 2015
Event8th IFIPWG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2014 - Beijing, China
Duration: Sep 16 2014Sep 19 2014

Publication series

NameIFIP Advances in Information and Communication Technology
Volume452
ISSN (Print)1868-4238

Other

Other8th IFIPWG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2014
CountryChina
CityBeijing
Period9/16/149/19/14

Keywords

  • Grain counting
  • Multi-threshold segmentation
  • Otsu
  • RBGM gradient Descent

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