Research of Dynamic Identification Technology on Cotton Foreign Fibers - Computer and Computing Technologies in Agriculture IV - Part III Access content directly
Conference Papers Year : 2011

Research of Dynamic Identification Technology on Cotton Foreign Fibers

Shuangxi Liu
  • Function : Author
  • PersonId : 1012857
Wenxiu Zheng
  • Function : Author
  • PersonId : 1012910
Hengbin Li
  • Function : Author
  • PersonId : 1012911
Jinxing Wang
  • Function : Author
  • PersonId : 988296

Abstract

Due to the low efficiency, large errors and other practical issues of manual sorting selection method, a new cotton foreign fiber analysis instrument was developed. After fully-smashing by the ginned cotton machine, the uninterrupted uniform cotton layer was formed, and then the image of the flow cotton layer was collected by line scanning camera. Firstly the gray-scale processing is carried on to the original cotton foreign fibers image. Moreover, some other treatment such as adaptive threshold method, filter technique and enhancement processing, are used to complete the image segmentation in order to obtain clear binary image; then hollowed inner point method and neighborhood search method are used to extract the contours in order to obtain the characteristic parameters of foreign fibers. Finally the category identification and weight statistics of foreign fibers is completed based on rough sets theory. It’s proved by experiments that the detection speed of this new instrument can achieve 40m/h and the recognition precision of this analyzer can achieve 90%.
Fichier principal
Vignette du fichier
978-3-642-18354-6_46_Chapter.pdf (159.41 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01563485 , version 1 (17-07-2017)

Licence

Attribution

Identifiers

Cite

Shuangxi Liu, Wenxiu Zheng, Hengbin Li, Jinxing Wang. Research of Dynamic Identification Technology on Cotton Foreign Fibers. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.379-389, ⟨10.1007/978-3-642-18354-6_46⟩. ⟨hal-01563485⟩
56 View
54 Download

Altmetric

Share

Gmail Facebook X LinkedIn More