Automated Ripeness Assessment System of Tomatoes Using PCA and SVM Techniques

Citation:
Esraa Elhariri, N. Elbendary, A. E. Hassanien, and A. Badr, "Automated Ripeness Assessment System of Tomatoes Using PCA and SVM Techniques", Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, USA, IGI, pp. 101-131, 2014.

Abstract:

One.of.the.prime.factors.in.ensuring.a.consistent.marketing.of.crops.is.product.quality,.and.the.process.of.
determining.ripeness.stages.is.a.very.important.issue.in.the.industry.of.(fruits.and.vegetables).production,.
since.ripeness.is.the.main.quality.indicator.from.the.customers’.perspective..To.ensure.optimum.yield.of.
high.quality.products,.an.objective.and.accurate.ripeness.assessment.of.agricultural.crops.is.important..
This.chapter.discusses.the.problem.of.determining.different.ripeness.stages.of.tomato.and.presents.a.
content-based.image.classification.approach.to.automate.the.ripeness.assessment.process.of.tomato.via.
examining.and.classifying.the.different.ripeness.stages.as.a.solution.for.this.problem..It.introduces.a.
survey.about.resent.research.work.related.to.monitoring.and.classification.of.maturity.stages.for.fruits/
vegetables.and.provides.the.core.concepts.of.color.features,.SVM,.and.PCA.algorithms..Then.it.describes.
the.proposed.approach.for.solving.the.problem.of.determining.different.ripeness.stages.of.tomatoes..The.
proposed.approach.consists.of.three.phases,.namely.pre-processing,.feature.extraction,.and.classification.
phase..The.classification.process.depends.totally.on.color.features.(colored.histogram.and.color.moments),.
since.the.surface.color.of.a.tomato.is.the.most.important.characteristic.to.observe.ripeness..This.approach.
uses.Principal.Components.Analysis.(PCA).and.Support.Vector.Machine.(SVM).algorithms.for.feature.
extraction.and.classification,.respectively

DOI:

10.4018/978-1-4666-6030-4.ch001