Criminal Face Identification System in Cloud Computing

DOI : 10.17577/IJERTCONV7IS11060

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Criminal Face Identification System in Cloud Computing

M. Deepthi

Dept of CSE

Besant Theosophical College

Abstract:- Criminal record generally contains personal information about particular person along with photograph. To identify any Criminal we need some identification regarding person, which are given by eyewitness. In most cases the quality and resolution of the recorded image segments is poor and hard to identify a face. To overcome this sort of problem we are developing software. Identification can be done in many ways like finger print, eyes, DNA etc. One of the applications is face identification. The face is our primary focus of attention in social inters course playing a major role in conveying identify and emotion. Although the ability to infer intelligence or character from facial appearance is suspect, the human ability to recognize face is remarkable.

INTRODUCTION:

This project is aimed to identify the criminals in any investigation department. Here the technique is we already store some images of the criminals in our database along with his details and that images are segmented into many slices say eyes, hairs, lips, nose, etc. These images are again stored in another database record so to identify any criminals; eyewitnesses will see the images or slices that appear on the screen by using it we develop the face, which may or may not be matched with our images. If any image is matched up to 99% then we predict that he is only the criminal. Thus using this project it provides a very friendly environment for both operator and eyewitness to easily design any face can identify criminals very easy.

PROBLEM AREA DESCRIPTION

The project is aimed at identifying the criminals with the help of eye witness. There are mainly four modules in our project. They are Adding, Deleting, Updating and identifying the criminals. There are mainly three roles in our project. They are:

  • Administrator

  • Operator

  • Eyewitness

The administrator is responsible for providing User ids and passwords. He provides authentication to the users. He creates deletes and Updates the User ids and Password.

The operator, who belongs to the investigating department, is responsible for entering the criminal details and maintains them. He adds, deletes and updates the criminal details. He also constructs the criminal face with the help of eye witness.

The eyewitness identifies the criminals with the help of cropped parts stored in a different database by the operator.

The eyewitness selects a cropped part from the database and that cropped part will be freeze by the operator in this way, complete face of the criminal is constructed and the details of that criminal is retrieved from the database. We can also construct a new image from those cropped parts which we consider as an imaginary face of the criminal.

PROJECT OBJECTIVE:

This project is intended to identify a person using the images previously taken. The identification will be done according the previous images of different persons.

PROJECT SCOPE:

The scope of the project is confined to store the image and store in the database. When a person has to be identified the images stored in the database are compared with the existing details.

OVERVIEW OF THE PROJECT:

This project is aimed to identify the criminals in any investigation department. Here the technique is we already store some images of the criminals in our database along with his details and those images are segmented into many slices say eyes, hairs, lips, nose, etc. These images are again stored in another database record so to identify any criminals; eyewitnesses will see the images or slices that appear on the screen by using it we develop the face, which may or may not be matched with our images. If any image is matched up to 99% then we predict that he is only the criminal. Thus using this project it provides a very friendly environment for both operator and eyewitness to easily design any face can identify criminals very easy.

SYSTEM ANALYSIS

The first step in developing anything is to state the requirements. This applies just as much to leading edge research as to simple programs and to personal programs, as well as to large team efforts. Being vague about your objective only postpones decisions to a later stage where changes are much more costly. The problem statement should state what is to be done and not how it is to be done. It should be a statement of needs, not a proposal for a solution. A user manual for the desired system is a good problem statement. The requestor should indicate which features are mandatory and which are optional, to avoid overly constraining design decisions. The requestor should avoid describing system internals, as this restricts implementation flexibility. Performance specifications and

protocols for interaction with external systems are legitimate requirements. Software engineering standards, such as modular construction, design for testability, and provision for future extensions, are also proper.

Many problems statements, from individuals, companies and government agencies, mixture requirements with design decisions. There may sometimes be a compelling reason to require a particular computer or language; there is rarely justification to specify the use of a particular algorithm. The analyst must separate the true requirements from design and implementation decisions disguised as requirements. The analyst should challenge such pseudo requirements, as they restrict flexibility. There may be politics or organizational reasons for the pressure requirements, but at least the analyst should recognize that these externally imposed design decisions are not essential features of the problem domain.

A problem statement may have more or less detail. A requirement for a conventional product, such as a payroll program or a billing system, may have considerable detail. A requirement for a research effort in a new area may lack many details, but presumably the research has some objective, which should be clearly stated.

EXISTING SYSTEM:

This system is manual system only. Here, have a facility to store the criminal images. If you want to compare the criminal images with the existing images it is manual process. This process is very slow to give the result. It is very critical to find the criminal images.

PROPOSED SYSTEM:

To overcome the drawbacks that were in the existing system we develop a system that will be very useful for any investigation department. Here the program keeps track of the record number of each slice during the construction of identifiable human face and calculate maximum number of slices of the similar record number. Based on this record number the program retrieves the personal record of the suspect (whose slice constituted the major parts of the constructed human face) on exercising the locate option.

ADVANTAGES:

  • Very fast and accurate.

  • No need of any extra manual effort.

  • No fever of data loss.

  • Just need a little knowledge to operate the system.

  • Doesnt require any extra hardware device.

  • At last very easy to find the criminals.

    OVERVIEW:

    Addition, Clipping, Construction and updating of the criminal record and face. Comparing the image with the faces that are there in our database. If any new images are found then it should be entered into our database by add image module and then it should be segmented into different slices.

    FUTURE ENHANCEMENTS

    The Future ehancements of this project include the following:

  • The criminal photos may be of any size.

  • By selecting any one cropped part of the criminal, we can get the full image of the criminals along

    with details.

  • New face constructed by different cropped parts can be saved.

CONCLUSION

The system can features an image processing where the input image can made less blurry so the s ystem can detect face on lower quality images .other than the system can use the data base which contains the personal information of the database. So whenever CFIS recognize a face. It will display the details of the user.

REFERENCES:

  1. Yulong Xu, Jiabao Wang, Yang Li, Zhuang Miao and Yafei Zhang, One-step backtracking for occlusion detection in real- time visual tracking, Electronics Letters ,Vol. 53 issue : 5, pp no:318320, 2nd March 2017.

  2. Yayu Zhai, Ping Song, (Member, Ieee), Zonglei Mou, Xiaoxiao Chen, And Xiongjun Liu, Occlusion-Aware Correlation Particle Filter Target Tracking Based on RGBD Data, IEEE Access, Vol: 6, pp no: 50752 50764, 2018.

  3. Jiyan Pan, BoHu and JianQiu Zhang,Robust and Accurate Object Tracking Under Various Types of Occlusions, IEEE Transactions On Circuits And Systems For Video Technology,

    Vol. 18, NO. 2, pp no: 223 – 236 February, 2008.pushpa\

  4. Xingping Dong, Jianbing Shen, Senior Member, IEEE, Wenguan Wang, and Hua Huang, Occlusion-aware Real-time Object Tracking by Integrated Circulant Structure Kernels Classifier, IEEE Transactions on Multimedia, Vol: 19 , Issue: 4 pp no: 763 771, 2017.

  5. Muhammad Imran Shehzad , Yasir A. Shah, Zahid Mehmood, Abdul Waheed Malik, Shoaib Azmat, K-means based multiple objects tracking with long-term occlusion handling, IET Computer Vision, Volume: 11 , Issue: 1, pp: 68 77, 2017.

  6. Chao Zhu and Yuxin Peng, A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling, IEEE Transactions On Image Processing, Vol:24, Issue: 12, pp no: 5619

5629, 2015

.

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