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作 者:卢亚辉 张纬华 和飞飞 王帅 郝锦虎 杜玉红[2] Lu Yahui;Zhang Weihua;He Feifei;Wang Shuai;Hao Jinhu;Du Yuhong(63966 Unit,Beijing 100071,China;School of Mechanical Engineering,Tiangong University,Tianjin 300380,China)
机构地区:[1]中国人民解放军63966部队,北京100071 [2]天津工业大学机械工程学院,天津300380
出 处:《机电工程技术》2023年第2期163-167,共5页Mechanical & Electrical Engineering Technology
摘 要:作战试验是当前部队工作的研究重点,其在数据采集、数据处理及数据识别过程中会产生大量的音视频文件及图片。对这些图像数据的分析结果表明,存在某些图片不清晰、视频数据采集不方便、数据识别结果不准确等问题。因此,为进行作战试验领域的深入研究,对这一过程中所用到的数据采集技术和数据处理识别技术进行探究和改进,从拍摄设备选型和数据采集指导两个方面对数据采集进行分析,提出了图像转化、图像二值化、图像平滑去噪、图像分割和图像边缘检测等主要图像预处理操作,并采用YOLO算法和SSD算法分别建立图像识别模型,通过对采集图像的试验获得了相关实验结果,所提方法有助于指导作战试验工作的开展,提升试验鉴定数据处理及分析能力,增强数据管理控制效能,以至极大拓展数据的利用率,提高作战工作的效率和准确度。Combat test is the current research focus of the army, and a large number of audio and video files and pictures are generate in the process of data collection, data processing and data identification. The analysis results of these image data show that there are some problems such as unclear pictures, inconvenient video data collection, and inaccurate data recognition results. Therefore, in order to conduct in-depth research in the field of combat testing, the data acquisition technology and data processing and identification technology used in the process were studied. The data acquisition was analyzed from the selection of shooting equipment and the guidance of data acquisition, the main image preprocessing operations such as image transformation, image binarization, image smoothing and denoising, image segmentation and image edge detection were proposed, and YOLO algorithm and SSD algorithm were used to establish image recognition models respectively. The relevant experimental results were obtained. The proposed method will help guide the development of the combat test work, improve the data processing and analysis capabilities of the test identification, enhance the efficiency of data management and control, and greatly expand the utilization rate of data, and improve the efficiency and accuracy of combat work.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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