Shape Feature Extraction of Wheat Leaf Disease Based on Invariant Moment Theory - Computer and Computing Technologies in Agriculture V - Part II Access content directly
Conference Papers Year : 2012

Shape Feature Extraction of Wheat Leaf Disease Based on Invariant Moment Theory

Zhihua Diao
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  • PersonId : 988245
Anping Zheng
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  • PersonId : 988246
Yuanyuan Wu
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  • PersonId : 988247

Abstract

Shape feature extraction is a key research direction on wheat leaf disease recognition. In order to resolve the problem of translation, scaling and rotation transformation invariance on shape matching, the invariant moment theory was introduced to shape feature extraction and seven Hu invariant moment parameters were defined as shape features. Meanwhile the present algorithm was used and new parameters were defined for shape feature extraction research on wheat leaf disease image. The shape features suitable for two types of wheat leaf disease recognition were received and applied in wheat disease intelligent recognition system. The results show that the system recognition rate is relatively high, and can meet the practical application requirements.
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hal-01360977 , version 1 (06-09-2016)

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Zhihua Diao, Anping Zheng, Yuanyuan Wu. Shape Feature Extraction of Wheat Leaf Disease Based on Invariant Moment Theory. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. pp.168-173, ⟨10.1007/978-3-642-27278-3_18⟩. ⟨hal-01360977⟩
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