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Multispectral Image Segmentation for Fruit Quality Estimation
Adolfo Martínez-Usó, Filiberto Pla, Pedro García-Sevilla
51 - 58
Frontiers in Artificial Intelligence and Applications
Volume 131: Artificial Intelligence Research and Development
Abstract

An unsupervised segmentation algorithm based on a multiresolution method is presented. This method uses variational functions as a segmentation criterion. The algorithm has been applied to multispectral images of fruits as a quality assessment application. In addition, due to the unsupervised nature of the procedure, it can be applied to real images in order to test the quality of these results.

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