International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
CRIMINAL IDENTIFICATION USING ARM7 Dr. Vijay Patil1 Shripad Tople2, Dinesh Wadje3, Vivek Motwani4 1Professor,
Dept. of Electronics and Telecommunication, PCCOE, Pune, India. student, Dept. of Electronics and Telecommunication, PCCOE, Pune, India. 3U.G. student, Dept. of Electronics and Telecommunication, PCCOE, Pune, India. 4U.G. student, Dept. of Electronics and Telecommunication, PCCOE, Pune, India. 2U.G.
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Abstract - Personal information of a person and
photograph is mainly used in criminal records. For identification of any criminal some identification marks regarding that person, given by eyewitness are needed. Many times it happens that the quality and resolution of the image recorded is poor and it becomes hard to recognize a face from it. This paper presents development of a software to overcome such kinds problem. Identification is possible through various ways such as, finger print, eyes, DNA etc. Most important of all applications is face recognition. Face is the prime center of attention in any social intercourse and plays the most vital role in conveying identity and expression. Though it is difficult to judge the mental ability or character from facial appearance , human beings can recognize several things from it significantly. This proposed system mainly consist of ARM7, GSM, GPS and camera interfacing. The cameras are placed in public places. If criminal's face gets detected in the camera, then connected computer will send signal to controller. Microcontroller will then send the location of criminal to predefined mobile number through GSM module. Key Words: MATLAB etc.
Criminal identification, ARM7, GSM, GPS,
1. INTRODUCTION The identification of criminals and terrorist is primary issue for police, Military and security forces. The terrorist activities and crime rate is increasing abnormally. To combat with these for identification of criminals & terrorists is a challenging task for all security departments. Security issue and protection of lives and public property are the primary concerns for all security departments. These departments are now-a-days using latest technology. This paper is an attempt to use data mining concept and will provide comprehensive data base of criminals and terrorist and will be great support for all above mentioned departments. To help the security forces data mining concepts proved to yield better results in this direction. This system uses a combination of location detection and face recognition. Face is one of the most prominent biometric identification techniques, to identify criminals. Today whole world is suffering from increasing terrorist Š 2017, IRJET
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Impact Factor value: 5.181
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and criminal activities and causes a major threat to the security of a country and its civilians. To identify terrorist and criminals and record their details, security and law enforcement agencies should have the necessary technology when a suspect is apprehended. As human beings, have the inborn ability to recognize and distinguish between faces. However, this kind of intelligence is not available yet with computers. In order to emulate this kind of problem it needs training. Researchers and software developers have develop various applications in which different algorithms and mathematical modules are implemented for criminal/terrorist identification. Face detection is a computer technology that determines The locations and sizes of human faces in arbitrary images are determined by face detection algorithm which detects facial features and ignores anything else, such as trees, bodies and buildings etc[1][2]. This system recognizes faces from images with some near real-time variations and proved to be efficient system. The systems implements and verify the algorithm. The approach consist of weighting the difference between a mean image, which is obtained by averaging a predefined set of faces and a given face image. The training set is a group of face images from which the mean face is calculated. The weighting difference between set of eigenvectors and linear projection of image on low dimensional image space is obtained for weighted Face detection.[3] Face recognition: Face recognition scheme of human identification is probably the most user friendly and nonintrusive authentication method available and is one of the most acceptable biometric techniques utilized in various real-world applications. The developing of face recognition system is quite difficult because the human face is quite complex, multidimensional and corresponding on environment changes. This research is focused on developing the versatile computational model of face recognition which is accurate, simple and fast when implemented in different environments. Here, the use of SIFT algorithm for face detection is recommended. This is most successful techniques that have been used to recognize faces in images. However, a major problem of this technique is dimensionality large and high computational cost .
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