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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Cotton Production and Processing Research » Research » Publications at this Location » Publication #342459
Research Project: Enhancing the Profitability and Sustainability of Upland Cotton, Cottonseed, and Agricultural Byproducts through Improvements in Pre- and Post-Harvest Processing

Location: Cotton Production and Processing Research

Title: Image processing for stripper harvested cotton trash content measurement a progress report

Author
item Pelletier, Mathew
item Barker, Gary
item Baker, Roy

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/3/1999
Publication Date: N/A
Citation: Pelletier, M.G., Barker, G.L., Baker Jr, R.V. 1999. Image processing for stripper harvested cotton trash content measurement a progress report. National Cotton Council Beltwide Cotton Conference. Vol. 2:1412-1415.

Interpretive Summary:

Technical Abstract: This study was initiated to provide the basis for obtaining on-line information as to the levels of the various types of gin trash. The objective is to provide the ginner with knowledge of the quantity of the various trash components in the raw uncleaned seed cotton. This information is currently not available to the ginner for use in optimizing the gin machinery. An existing Kodak trilinear array color ccd line scan imager was connected to a PC in a laboratory environment. Due to the high levels of trash in stripper harvested cotton, an 8.0 in. by 10.0 in. viewing area was used. Images of seed cotton (taken from various stages in the pre-ginning cleaning process) were obtained without pressing the seed cotton against glass plates. This omission, of a standard cotton image acquisition technique, increases the opportunities for image acquisition in the gin to obtain the gin trash levels for use in optimal gin control by removing the necessity of capturing a sample of seed cotton to press against an imaging plate. Algorithms were developed to differentiate between: seed cotton, the various trash components and the background. Once the individual components were identified, an algorithm was developed to determine the levels of the various trash components; sticks, burrs, and leaves.