Machine grading and blemish detection in apples

G. Rennick; Y. Attikiouzel; A. Zaknich

doi:10.1109/ISSPA.1999.815736

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Machine grading and blemish detection in apples

Conference paper

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Machine grading and blemish detection in apples

G. Rennick, Y. Attikiouzel and A. Zaknich

ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359), Vol.2, pp.567-570

IEEE

Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, ISSPA '99 (Brisbane, Australia, 22/08/1999–25/08/1999)

1999

DOI: https://doi.org/10.1109/ISSPA.1999.815736

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Abstract

Five classifiers including the K-means, fuzzy c-means, K-nearest neighbour, multi-layer perceptron neural network and probabilistic neural network classifiers are compared for application to colour grade classification and detection of bruising of granny smith apples. A number of suitable discriminate features are determined heuristically for the categorisation of four classes including: high grade fruit, high grade fruit with bruising or blemishes, off-grade fruit, and off-grade fruit with bruising or blemishes. Robust features based on intensity statistics are extracted from enhanced monochrome images produced by special transformation from original RGB images. The best of the five classifiers using the optimal feature set, is shown to outperform human graders viewing the same images

Details

Title: Machine grading and blemish detection in apples
Authors/Creators: G. Rennick (Author/Creator) - The University of Western Australia
Y. Attikiouzel (Author/Creator) - Department of Physics, Mathematics and Informatics
A. Zaknich (Author/Creator) - Department of Physics, Mathematics and Informatics
Publication Details: ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359), Vol.2, pp.567-570
Conference: Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, ISSPA '99 (Brisbane, Australia, 22/08/1999–25/08/1999)
Publisher: IEEE
Identifiers: 991005542328207891
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Conference paper

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