Chromatic Image Analysis for Cotton Trash and Color Measurements

Xu, Bugao; Chen, Fang; Huang, R.K.; Watson, Michael D.

doi:10.1177/004051759706701204

Cited by 36 publications

(21 citation statements)

References 3 publications

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“…Xu et al used CCD cameras and Xenon illumination to show a strong correspondence between CCD, HVI, and human grading on estimates of foreign matter content and cotton color measurements [5]. Later studies by Yang et al combined color and ultraviolet (UV) illumination for foreign matter detection and achieved a mean detection accuracy of 92.34% using both color and shape features [6,7].…”

Section: Introductionmentioning

confidence: 99%

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

Kuzy

2017

Sensors

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Detection of foreign matter in cleaned cotton is instrumental to accurately grading cotton quality, which in turn impacts the marketability of the cotton. Current grading systems return estimates of the amount of foreign matter present, but provide no information about the identity of the contaminants. This paper explores the use of pulsed thermographic analysis to detect and identify cotton foreign matter. The design and implementation of a pulsed thermographic analysis system is described. A sample set of 240 foreign matter and cotton lint samples were collected. Hand-crafted waveform features and frequency-domain features were extracted and analyzed for statistical significance. Classification was performed on these features using linear discriminant analysis and support vector machines. Using waveform features and support vector machine classifiers, detection of cotton foreign matter was performed with 99.17% accuracy. Using frequency-domain features and linear discriminant analysis, identification was performed with 90.00% accuracy. These results demonstrate that pulsed thermographic imaging analysis produces data which is of significant utility for the detection and identification of cotton foreign matter.

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Section: Introductionmentioning

confidence: 99%

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

Kuzy

2017

Sensors

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“…Apart from the factors mentioned earlier, the colour of cotton can be affected by: staining through contact with the soil, grass, etc., as well as by conditions of cotton storage (e.g. moisture and temperature) [7,19]. That being so, the deterioration in colour indicates the lower processing efficiency and, at the same time, lowers market value of cotton.…”

Section: Introductionmentioning

confidence: 99%

Digieye Application In Cotton Colour Measurement

Matusiak

2015

Autex Research Journal

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Colour is one of the most important properties of cotton raw materials. It helps in determining and classifying the quality of fibres according to the Universal Cotton Standards. Organoleptic and instrumental techniques are applied to assess the color of cotton. Worldwide, the colour parameters of cotton are measured by the High Volume Instrument (HVI), which provides information on reflectance (Rd) and yellowness (+b) that is specific for cotton, but are not the typical and globally recognized colour characteristics. Usually, worldwide, the colour of textile products and other goods is assessed utilizing the spectrophotometer, which provides the colour data that is widely recognized and accepted by the CIE L*a*b* colour space. This paper discusses utilizing the DigiEye system to measure the colour parameters of cotton samples and compares the results with the colour parameters from the HVI.

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“…The precision and accuracy of HVI measurements are highly sensitive to sample preparation and handling, and, hence cannot be used as a reliable means to quantify the amount of trash present. Recent research efforts exploring the use of better separation machinery [2], color scanners [3], [4], and more effective sample preparation mechanisms [5] have generated only incremental improvements.…”

Section: Introductionmentioning

confidence: 99%

Segmentation and classification of four common cotton contaminants in x-ray microtomographic images

Pavani

Dogan

Sari‐Sarraf

et al. 2004

Machine Vision Applications in Industrial Inspection XII

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Technologies currently used for cotton contaminant assessment suffer from some fundamental limitations. These limitations result in the misassessment of cotton quality and may have a serious impact on the evaluation of the economic value of the cotton crop. This paper reports on the recent advances in the use of a 3D x-ray microtomographic system that employs image processing and pattern recognition techniques to accurately detect and classify trash present in cotton. The proposed method offers an attractive alternative to existing trash evaluation technologies, because of its ability to produce 3D representations of the samples, to robustly segment the trash from its background, and to accurately classify the contaminant types. This procedure, could have a serious impact on the process control technologies (cotton lint cleaning), and indeed on the economic value of cotton.

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Chromatic Image Analysis for Cotton Trash and Color Measurements

Cited by 36 publications

References 3 publications

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

Digieye Application In Cotton Colour Measurement

Segmentation and classification of four common cotton contaminants in x-ray microtomographic images

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