Distinguishing onion leaves from weed leaves based on segmentation of color images and a BP neural network

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Abstract

A new algorithm to distinguish onion leaves from weed leaves in images is suggested. This algorithm is based on segmentation of color images and on BP neural network. It includes: discarding soil for conserving only plants in the image, color image segmentation, merging small regions by analyzing the frontier rates and the averages of color indices of the regions, at last a BP neural network is used to determine if the small regions belongs to onion leaf or not. The algorithm has been applied to many images and the correct identifiable percents for onion leaves are between 80%-90%. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Lu, J. W., Gouton, P., & Hu, Y. A. (2006). Distinguishing onion leaves from weed leaves based on segmentation of color images and a BP neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 349–354). Springer Verlag. https://doi.org/10.1007/11760023_51

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