Research on Recognition of Fertilized Egg Based on Optimized LVQ by Genetic Algorithm

Jian Yang; Chun Yan Xia; Xiu Ying Li; He Pan; Ying Shi

doi:10.4028/www.scientific.net/AMM.472.522

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 472Research on Recognition of Fertilized Egg Based on...

Research on Recognition of Fertilized Egg Based on Optimized LVQ by Genetic Algorithm

Abstract:

In order to detect fertilized eggs nondestructively to improve hatching rate, this paper uses the method of image processing and Learning Vector Quantization neural network to identify fertilized eggs. Firstly, we use image collection device to collect images of the unfertilized and fertilized eggs and extract the feature of egg image, and then determine 5 principal component characteristics of the egg shape. Learning vector quantization neural networkis 5 dimensional input and 1 dimensional outputs.Finally,we use Genetic Algorithm to optimize the weights and threshold of neural network, which can be used to predict the condition of fertilization. The experiment shows that, compared with the traditional LVQ neural network, it is more accurate to recognize the fertilized eggs when using optimized LVQ neural network by genetic algorithm. The rate can reach 98.21%, which meets therequirements of recognizing fertilized eggs.

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Periodical:

Applied Mechanics and Materials (Volume 472)

Pages:

522-526

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.472.522

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Online since:

January 2014

Authors:

Jian Yang, Chun Yan Xia, Xiu Ying Li, He Pan, Ying Shi

Keywords:

Egg Freshness, Genetic Algorithm (GA), LVQ Neural Network, Nondestructive Testing (NDT)

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