基于Fisher准则函数的凝聚相炸药爆炸火光图像识别研究

Pattern Recognition for Images of Explosion Fireball of Condensed Explosives Based on Fisher Criterion

为研究利用爆炸火光常规RGB图像识别炸药类型的可行性,以30g小药量凝聚相炸药爆炸火光的高速摄像图片为对象,提取爆炸火光高光区域的面积时程曲线,用面积时程曲线的形态特征参数建立了描述凝聚相炸药爆炸火光的多维特征向量空间,采用经过推广的三类问题的Fisher准则函数和Bayes决策规则确定了具有最佳识别特征向量的三类问题的线性识别模式,并对试验样本集进行TNT、RDX、HMX三类炸药识别。结果表明:检测样本集对训练样本集所确立的线性识别模式的误判率的检测结果为10.07%,在全样本空间,利用自析方法所检测的线性识别模式的误判率为17.48%,识别效率较高。

To investigate the feasibility of discriminating explosive type with RGB image of fireball of explosion, the curves of time vs area with intensive light on the images were obtained on the basis of a lot of photographs of explosion of condensed explosive with small dosage （30 g） by the high speed photography, and multi-dimension eigenveetor space to describe firelight of explosion of condensed explosives was built by using feature parameters of configurations of curves of area vs time. And finally the linear three-type pattern recognition with optimal eigenvector was made by applying three-type Bayes＇s decision rule and generalized fishe~ criterion. The test data of TNT, RDX, HMX were discriminated. Results show that the inaccuracy is 10.07% of pattern recognition built by the training set, while it is 17.48% of pattern recognition with using Jackknifing method in the total sample sets.