Automated Criminal Identification by Face Recognition using Open Computer Vision Classifiers

P. Apoorva, H. C. Impana, S. Siri, M. Varshitha., B. Ramesh
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引用次数: 32

Abstract

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.
基于开放计算机视觉分类器的人脸识别罪犯自动识别
本文介绍了一种基于自动监控摄像头的实时人脸识别系统。该系统包括4个步骤,包括(1)实时图像的训练(2)haar分类器的人脸检测(3)训练后的实时图像与监控摄像头图像的比较(4)基于比较的结果。我们感兴趣的一个重要应用是自动监视,其目的是识别监视名单上的人。本文的目标是将一幅图像与已经训练好的几幅图像进行比较。本文提出了一种实时环境下的鲁棒人脸检测方法。哈尔级联算法是人脸检测中的一种算法。这里我们使用Haar类分类器在OpenCV平台上跟踪人脸。人脸识别的准确率非常高。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。在印度,我们有一个识别公民的系统,叫做Aadhaar。如果我们将其用作公民身份数据库,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犯罪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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