包晓安, 张瑞林, 钟乐海. 基于人工神经网络与图像处理的苹果识别方法研究[J]. 农业工程学报, 2004, 20(3): 109-112.
    引用本文: 包晓安, 张瑞林, 钟乐海. 基于人工神经网络与图像处理的苹果识别方法研究[J]. 农业工程学报, 2004, 20(3): 109-112.
    Bao Xiao′an, Zhang Ruilin, Zhong Lehai. Apple grade identification method based on artificial neural network and image processing[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(3): 109-112.
    Citation: Bao Xiao′an, Zhang Ruilin, Zhong Lehai. Apple grade identification method based on artificial neural network and image processing[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(3): 109-112.

    基于人工神经网络与图像处理的苹果识别方法研究

    Apple grade identification method based on artificial neural network and image processing

    • 摘要: 针对中国苹果等级划分主要依靠人工感官进行识别判断的现状,提出了以应用计算机视觉以及图像处理技术为基础,通过改变传统学习向量量化(LVQ)网络输入层各参数的权重来改变其在竞争层中的竞争能力。采用改进后的LVQ网络算法,对苹果进行等级判别试验,取得了良好的试验结果,识别正确率达88.9%,且具有较好的稳定性。

       

      Abstract: In view of the drawbacks of apple grade identification in China, which still relies on human sense organs, ths paper presents a processing method on the basis of the technology of computer vision and digital image. The method of grade identification can change the competitiveness of the parameters by changing the weights of parameters in input layer of the Learning Vector Quantization(LVQ). The improved LVQ neural network algorithm was applied in the process to identify the grade of apples, which was proved effective by experiment, reaching the correct identification rate of 88.9% with good stability.

       

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