An active contour computer algorithm for the classification of cucumbers

The cucumber is one of the most important crops worldwide and, because it is generally consumed fresh, it must be classified into quality categories. The European classification system includes a parameter that relates the degree of curvature relative to the length. Until now, this classification co...

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Veröffentlicht in:	Computers and electronics in agriculture Jg. 92; S. 75 - 81
Hauptverfasser:	Clement, Javier, Novas, Nuria, Gazquez, José-Antonio, Manzano-Agugliaro, Francisco
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.03.2013 Elsevier
Schlagworte:	Agronomy. Soil science and plant productions algorithms Artificial vision Biological and medical sciences crops Cucumber cucumbers Curvature Fundamental and applied biological sciences. Psychology Grading humans Length Shape Shape Grading Length Cucumber Curvature Artificial vision Cucurbitaceae Cucumis sativus Algorithm Vegetable crop Dicotyledones Angiospermae Classification Spermatophyta Active contour
ISSN:	0168-1699, 1872-7107
Online-Zugang:	Volltext
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Abstract	The cucumber is one of the most important crops worldwide and, because it is generally consumed fresh, it must be classified into quality categories. The European classification system includes a parameter that relates the degree of curvature relative to the length. Until now, this classification could not been be achieved with an automatic system due to the difficulty associated with correctly calculating the axis of a cucumber. This article describes a computer algorithm that uses active contours or “snakes” to classify cucumbers by length and curvature. This algorithm demonstrates an advantage in the determination of the central line of each cucumber, based on an iterative process that is quick and carries out the classification process efficiently. The method was validated against human classification for 360cucumbers and was also compared with an ellipsoid approximation method. The active contour method reduced the classification error by 15% points, compared with the ellipsoid approximation method, to 1%, with no serious errors (i.e., misclassification of Class Extra and I into Class II or vice versa). Meanwhile, the ellipsoid approximation method led to a 16% error rate, of which 2% were serious errors (an error of two classes). The developed approach is applicable to fresh cucumber commercial classification lines to meet the requirements of the European regulations for cucumber classification.
AbstractList	► Cucumber is one of the most important crops worldwide, and is consumed raw. ► The European classification demands that both length and curvature are taken into account. ► A method has been developed that classifies according to curvature and length, based on active contours. ► The method gives classification errors of 1% with no serious errors. ► It is applicable to commercial classification lines of fresh cucumbers. The cucumber is one of the most important crops worldwide and, because it is generally consumed fresh, it must be classified into quality categories. The European classification system includes a parameter that relates the degree of curvature relative to the length. Until now, this classification could not been be achieved with an automatic system due to the difficulty associated with correctly calculating the axis of a cucumber. This article describes a computer algorithm that uses active contours or “snakes” to classify cucumbers by length and curvature. This algorithm demonstrates an advantage in the determination of the central line of each cucumber, based on an iterative process that is quick and carries out the classification process efficiently. The method was validated against human classification for 360cucumbers and was also compared with an ellipsoid approximation method. The active contour method reduced the classification error by 15% points, compared with the ellipsoid approximation method, to 1%, with no serious errors (i.e., misclassification of Class Extra and I into Class II or vice versa). Meanwhile, the ellipsoid approximation method led to a 16% error rate, of which 2% were serious errors (an error of two classes). The developed approach is applicable to fresh cucumber commercial classification lines to meet the requirements of the European regulations for cucumber classification. The cucumber is one of the most important crops worldwide and, because it is generally consumed fresh, it must be classified into quality categories. The European classification system includes a parameter that relates the degree of curvature relative to the length. Until now, this classification could not been be achieved with an automatic system due to the difficulty associated with correctly calculating the axis of a cucumber. This article describes a computer algorithm that uses active contours or “snakes” to classify cucumbers by length and curvature. This algorithm demonstrates an advantage in the determination of the central line of each cucumber, based on an iterative process that is quick and carries out the classification process efficiently. The method was validated against human classification for 360cucumbers and was also compared with an ellipsoid approximation method. The active contour method reduced the classification error by 15% points, compared with the ellipsoid approximation method, to 1%, with no serious errors (i.e., misclassification of Class Extra and I into Class II or vice versa). Meanwhile, the ellipsoid approximation method led to a 16% error rate, of which 2% were serious errors (an error of two classes). The developed approach is applicable to fresh cucumber commercial classification lines to meet the requirements of the European regulations for cucumber classification.
Author	Novas, Nuria Manzano-Agugliaro, Francisco Gazquez, José-Antonio Clement, Javier
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Keywords	Shape Grading Length Cucumber Curvature Artificial vision Cucurbitaceae Cucumis sativus Algorithm Vegetable crop Dicotyledones Angiospermae Classification Spermatophyta Active contour
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Snippet	► Cucumber is one of the most important crops worldwide, and is consumed raw. ► The European classification demands that both length and curvature are taken... The cucumber is one of the most important crops worldwide and, because it is generally consumed fresh, it must be classified into quality categories. The...
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SubjectTerms	Agronomy. Soil science and plant productions algorithms Artificial vision Biological and medical sciences crops Cucumber cucumbers Curvature Fundamental and applied biological sciences. Psychology Grading humans Length Shape
Title	An active contour computer algorithm for the classification of cucumbers
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