基于图像处理的人工神经网络在数字取证犯罪现场物体检测中的应用

Deepa Devasenapathy, M. Raja, R. K. Dwibedi, N. Vinoth, T. Jayasudha, V. D. Ganesh
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引用次数: 0

摘要

数字取证科学非常重视物体的检测,这是最重要的研究领域之一。一些行业和机构可能受益于目标检测方法,包括与医疗诊断扫描、交通监控、机场安全、执法以及本地和全球范围的数据救援有关的行业和机构。本研究旨在利用人工神经网络的各种增强、分割、特征提取、分类等方法,对视频监控图像中的武器进行检测,以提高检测精度。然而,计算了几个数学和算法模型来提供适当的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Neural Network using Image Processing for Digital Forensics Crime Scene Object Detection
Digital forensics science places a significant emphasis on the detection of objects as one of the most vital areas of study. Several industries and institutions may benefit from the object detection method, including those concerned with medical diagnostic scanning, traffic monitoring, airport security, law enforcement, and data rescue on a local and global scale. This study aims to detect weapons in video surveillance images by using various enhancement, segmentation, feature extraction, and classification methods by Artificial Neural Network to improve the detection accuracy. Yet, several mathematical and algorithmic models are computed to provide the appropriate approaches.
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