Lettuce Images Features Extraction and Intelligent Classification of Growth Period

Yan Wang; Jun Sun; Hong Li Wang; Ze Gao Dai; Wen Xia Lv

doi:10.4028/www.scientific.net/AMR.846-847.1351

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Lettuce Images Features Extraction and Intelligent...

Lettuce Images Features Extraction and Intelligent Classification of Growth Period

Abstract:

Classification of lettuce growth peroid is the premise of records of lettuce growth information. In this study, lettuce images in every growth period are collected. And visible images are preprocessed to extract features to establish initial feature library of lettuce images. Through R cluster analysis on many features, good image eigenvector are obtained. Classification of the lettuce samples are obtained by modeling and analysis of the neural networks. The experimental classification results compared with practical classification results, the recognition accuracy is up to 88.4%.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1351-1354

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1351

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Online since:

November 2013

Authors:

Yan Wang, Jun Sun*, Hong Li Wang, Ze Gao Dai, Wen Xia Lv

Keywords:

BP Network, Feature Extraction, Lettuce Image

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* - Corresponding Author

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