江苏大学学报（自然科学版）2013，Vol.34Issue(2)：171-177,7.DOI:10.3969/j.issn.1671-7775.2013.02.009
基于改进投影寻踪技术和模糊神经网络的未受精种蛋检测模型
Detection model of un-fertilized egg based on improved projection pursuit and fuzzy neural network
摘要
Abstract
To overcome the complexity and ambiguity of non-destructive detection characteristics for unfertilized eggs based on computer vision technology, an improved projection pursuit method combined with fuzzy neural network was proposed to decide whether the eggs were fertilized. The feature vector of complex shape of egg images was extracted to reduce the dimensionality by quantum projection pursuit technology. An improved quantum genetic algorithm was established to calculate the best projection direction. The non-destructive detection method was realized to diagnose whether the eggs were fertilized based on automatic decision inference rule of fuzzy neural network. The results show that the proposed method can meet actual testing requirements with high speed, good stability and robustness, and the accuracy can reach 99.37%.关键词
种蛋检测/投影寻踪/量子遗传算法/模糊神经网络/特征提取Key words
hatch egg identification/ projection pursuit/ quantum genetic algorithm/ fuzzy neural network/ feature extraction分类
信息技术与安全科学引用本文复制引用
关海鸥,杜松怀,许少华,左豫虎..基于改进投影寻踪技术和模糊神经网络的未受精种蛋检测模型[J].江苏大学学报（自然科学版）,2013,34(2):171-177,7.基金项目
国家自然科学基金资助项目(51177165) （51177165）
中国农业大学博士创新基金资助项目(2012YJ112) （2012YJ112）
黑龙江省农垦总局科技攻关项目(HNK11AZD-07-07) （HNK11AZD-07-07）
