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Automated Criminal Identification by Face Recognition using Open Computer Vision Classifiers

机译:使用开放式计算机视觉分类器通过人脸识别自动识别犯罪

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This paper presents a real time face recognition using a automated surveillance camera. The proposed system consists of 4 steps, including (1)training of real time images (2)face detection using Haar-classifier (3) comparison of trained real time images with images from the surveillance camera (4)result based on the comparison. An important application of interest is automated surveillance, where the objective is to recognize people who are on a watch list. The aspiration of this paper is to compare an image with several images which has been already trained. In this paper, we represent a methodology for face detection robustly in real time environment. Haar cascading is one of the algorithm for face detection. Here we use Haar like classifiers to track faces on OpenCV platform. The accuracy of the face recognition is very high. 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. In India, we have a system for recognizing citizen called Aadhaar. If we use this as a citizenship database we can differentiate between citizen and foreigner and further investigate whether the identified person is criminal or not.
机译:本文介绍了使用自动监控摄像头的实时人脸识别。所提出的系统包括4个步骤,包括(1)实时图像的训练(2)使用Haar分类器进行人脸检测(3)将经过训练的实时图像与来自监控摄像机的图像进行比较(4)基于比较的结果。感兴趣的重要应用是自动监视,其目的是识别监视列表中的人员。本文的目的是将一张图像与几张已经经过训练的图像进行比较。在本文中,我们代表了一种在实时环境中稳健地进行人脸检测的方法。 Haar级联是用于面部检测的算法之一。在这里,我们使用类似Haar的分类器来跟踪OpenCV平台上的人脸。人脸识别的准确性非常高。所提出的系统可以成功地识别多于一张的脸,这对于快速搜索可疑人员很有用,因为计算时间非常短。在印度,我们有一个称为Aadhaar的公民识别系统。如果将其用作公民数据库,我们可以区分公民和外国人,并进一步调查所识别的人是否为犯罪分子。

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