2014
DOI: 10.1002/ceat.201400208
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Gradient‐Direction‐Pattern Transform for Automated Measurement of Oil Drops in Images of Multiphase Dispersions

Abstract: The automated detection and measurement of oil drops in multiphase fermentation systems are important for mass transfer analysis. A novel computer technique for automated detection of oil drops in images is presented in the context of a stirred tank containing a three‐phase water‐oil‐air dispersion. The technique is an original feature extraction transform designed for the detection of objects with a characteristic appearance. The proposed transform, denominated gradient‐direction‐pattern (GDP) transform, util… Show more

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Cited by 5 publications
(2 citation statements)
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“…The approaches described here are very comparable to the work of Rojas‐Domínguez et al They proposed to transform the denominated gradient‐direction‐pattern (GDP). The GDP is as the described pattern matching algorithm right now only implemented to find circular patterns.…”
Section: Methodssupporting
confidence: 56%
“…The approaches described here are very comparable to the work of Rojas‐Domínguez et al They proposed to transform the denominated gradient‐direction‐pattern (GDP). The GDP is as the described pattern matching algorithm right now only implemented to find circular patterns.…”
Section: Methodssupporting
confidence: 56%
“…The approaches described here are comparable to the work of Rojas-Domínguez et al (2015). They propose a transformation of the denominated Gradient-DirectionPattern (GDP).…”
Section: Image Analysis Working Principlementioning
confidence: 93%