Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Machine grading and blemish detection in apples

Rennick, G., Attikiouzel, Y. and Zaknich, A. (1999) Machine grading and blemish detection in apples. In: Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, ISSPA '99, 22 - 25 August, Brisbane, Australia pp. 567-570.

PDF - Published Version
Download (354kB)
Link to Published Version:
*Subscription may be required


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

Item Type: Conference Paper
Publisher: IEEE
Copyright: © 1999 IEEE
Item Control Page Item Control Page


Downloads per month over past year