Recognition of Bullet Holes Based on Video Image Analysis

2017 International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Ruolin, Zhu^1 ; Jianbo, Liu^1 ; Yuan, Zhang^1 ; Xiaoyu, Wu^1

School of Information Engineering, Communication University of China, Beijing

10024, China^1

关键词: Bullet holes;    Convolutional neural network;    Digital videos;    Outdoor environment;    Shooting trainings;    Support vector machine algorithm;    SVM classifiers;    Video image analysis;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/261/1/012020/pdf
DOI  :  10.1088/1757-899X/261/1/012020

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The technology of computer vision is used in the training of military shooting. In order to overcome the limitation of the bullet holes recognition using Video Image Analysis that exists over-detection or leak-detection, this paper adopts the support vector machine algorithm and convolutional neural network to extract and recognize Bullet Holes in the digital video and compares their performance. It extracts HOG characteristics of bullet holes and train SVM classifier quickly, though the target is under outdoor environment. Experiments show that support vector machine algorithm used in this paper realize a fast and efficient extraction and recognition of bullet holes, improving the efficiency of shooting training.