基于卷积神经网络和时空特征的烟幕视频检测和参数提取

Smoke Screen Video Detection and Parameter Extraction Based on Convolutional Neural Network and Spatio-temporal Features

为提高干扰弹在战场上作战效能,摸清干扰弹的作战效能底数和极限施放条件,并修正干扰弹烟幕扩散方程。针对现有干扰弹作用过程形成的烟幕,烟幕透明特性和纹理各不相同,通用性较差,为能精准提取烟幕的烟幕轮廓和运动特征,提出一种基于卷积神经网络、烟幕时空特征的混合方法。该方法主要分为5个阶段:对YUV色彩空间的对比度调整;应用了差帧法检测输入视频图像序列的运动区域,设计了卷积神经网络体系结构框架,将运动区域通过卷积神经网络识别烟幕候选区域;根据烟幕的时空特征,从每个候选区域进一步识别烟幕候选区域;采用了支持向量机分类器,利用提取的特征对真实烟幕区域与非烟幕区域进行分类;提取烟幕特征的参数。经试验验证,所建立的模型将烟幕识别准确度最低提高至99.94%,能有效满足修正干扰弹作用过程中的烟幕扩散方程,为干扰弹的定型试验和作战应用提供了有力支持。

In order to enhance the operational effectiveness of jamming bomb on the battlefield,it is imperative to comprehend the fundamental characteristics and extreme deployment conditions of jamming bomb,and amend the smoke dispersion equation associated with jamming bomb.Nonetheless,given the inherent variability in the transparency and texture of jamming bomb during the operational deployment and its diverse appearance in different environmental contexts,there exists a significant challenge in accurately extracting the smoke s contour and motion features.To address this issue,a hybrid approach based on the convolutional neural networks and the spatiotemporal characteristics of smoke is proposed.The proposed method encompasses five distinct phases:Adjustment of contrast in YUV color space;Implementation of a frame difference method to detect the motion regions within the input video image sequence,employing a well-designed convolutional neural networks architecture to identify potential smoke regions within these motion regions;Utilization of the smoke s spatiotemporal characteristics to further discern potential smoke regions within each candidate area;Adoption of a support vector machine(SVM)classifier which employs the extracted features to classify real smoke regions from non-smoke regions;Extraction of smoke feature parameters.The experimental results show that the proposed model can be used to improve the accuracy of smoke recognition to at least 99.94%.Consequently,it effectively meets the requirements for adjusting the smoke dispersion equation during the operational deployment of jamming bombs,providing substantial support for the prototyping experiments and practical utilization of jamming bomb.