Segmentation of cucumber disease leaf image based on MDMP-LSM

Haiyang Jiang, Jian Zhang, Yuan Yuan, Miantao He, Shouguo Zheng

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

It is a crucial problem for crop disease diagnosing to effectively extract disease spots from crop pictures with complex background. To solve this problem, a new multiple domain multiple phase level set method is proposed. First, the spatial distribution characteristic that the disease spots to be segmented are statistically located in inner parts of crop leaves is adopted to build a multiple phase level set model with inner ordering. Then, to enhance segmentation effectivity for complex background cases, we adopt multiple spatial domains to the model for the first time so that inner and outer level set functions will evolve in different spatial domains. Experimental results show that this method can well extract disease spots for complex background cases with an accuracy rate of 93.3% and will be a good base for diagnoses.

Original languageEnglish
Pages (from-to)142-148
Number of pages7
JournalNongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Volume28
Issue number21
DOIs
StatePublished - 1 Nov 2012
Externally publishedYes

Keywords

  • Complex background
  • Crops
  • Diseases
  • Image segmentation
  • Level set method
  • Multiple domain multiple phase

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