第4章红枣缺陷检测40-45
4.1红枣图像的采集40-41
4.2红枣图像的处理41-42
4.3红枣图像缺陷的分割42-43
4.4缺陷有无的判别43-44
4.4.1确定判断依据43
4.4.2判断结果43-44
4.5小结44-45
第5章红枣纹理检测45-53
5.1纹理特征的提取45-47
5.1.1基于统计分析的纹理识别方法研究45-47
5.2材料与方法47-48
5.3红枣图片采集48
5.4红枣图像预处理48
5.5BP人工神经网络颜色分级48-50
5.5.1BP神经网络简介48-49
5.5.2BP神经网络的训练学习49-50
5.6BP神经网络的红枣纹理分级50-51
5.7纹理与水分试验51-52
5.8小结52-53
第6章红枣颜色检测53-61
6.1颜色模型的确定53-55
6.1.1RGB颜色模型54
6.1.2HSI颜色模型54-55
6.1.3颜色模型转换55
6.2颜色特征的提取55-57
6.2.1红枣图像采集56
6.2.2红枣图像背景分割56
6.2.3特征提取56-57
6.3RGB模型和HSI模型的红枣颜色分级57-59
6.3.1实验材料与方法57-58
6.3.2输入层设计58
6.3.3输出层设计58
6.3.4中间层设计与网络训练58
6.3.5分级结果58-59
6.4糖度与颜色的关系59-60
6.5小结60-61
第7章结论与展望61-63
7.1结论61-62
7.2展望62-63
附录63-70
参考文献70-75
致谢75-76
六、目前已经阅读的主要文献
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[3]周健华.红枣分级机的设计及试验研究[D].新疆农业大学,2012.
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