利用人脸识别和网页抓取识别罪犯和失踪儿童

S. Ayyappan, S. Matilda
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引用次数: 8

摘要

面部识别是一种基于生物特征的技术,它可以用数学方法绘制出个人的面部特征,并将数据存储为面部指纹。它在图像上使用机器学习并生成一个特征向量,该特征向量将一个对象映射为一组数字。谷歌和Facebook等组织使用这项技术为其用户创建数字档案。这个项目建议使用这项技术来识别那些在逃的罪犯。一份NCRB(国家犯罪记录局)的报告显示,70%的犯罪是由同一罪犯反复犯下的。这些罪犯可以通过安装在不同地点的摄像头拍摄的图像或视频帧的面部识别来识别,也可以用来识别失踪的儿童。缺点是图像通常是模糊的,清晰度较低,人眼无法识别。该系统可以成功地识别多张人脸,计算时间短,有利于快速搜索可疑人员。它为每个人脸创建一个独特的模板,并将它们与数据集中可用的其他图像进行比较。如果找到了输入人脸的匹配,那么将显示与相关图像相关联的详细信息。这一制度将减少犯罪,确保社会安全。
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Criminals And Missing Children Identification Using Face Recognition And Web Scrapping
Face recognition is a biometric based technology that maps an individual's facial features mathematically and stores the data as a face print. It employs Machine Learning on the image and generates a feature vector which maps an object with array of numbers. This technology is used by organizations such as Google and Facebook to create a digital profile for its users. This project proposes to use this technology for identifying criminals who are on the run from their previous records. An NCRB (National Crime Records Bureau) report shows that 70% of crimes are repeatedly committed by the same criminals. These criminals can be identified by the face recognition from an image or video frame which is captured by the cameras which are installed in various locations and it can also be used for identifying missing children. The disadvantage posed is that the images are usually blurred, have less clarity and not recognizable to the human eye. The proposed system can successfully recognize more than one face which is useful for quickly searching suspected persons as the computation time is very low. It creates a unique template for each face and compare them with other images available in dataset. If the match is found for the input face, then the details associated with the related image will be displayed. This system will decrease the crimes and ensure the security in our society.
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