Fake Face detection

Project Title

Fake Face detection

Project Area of Specialization Artificial IntelligenceProject Summary

Face detection is the issue of recognizing and checking people in a photograph by their face. It analyzes the face present in an image, when faces are changed by age or their facial structure the system declares it as fake . Eventually, it remains a PC vision issue for quite a while.

Deep learning techniques can use large datasets of faces and learn about the facial structure or portrayals of faces. The system uses the deep learning technique and AI to detect the faces in given images . 

Project Objectives

The fake or manipulated faces are being generated enormously which are harder to detect by traditional means of software or methods. The objectives of this project is to detect the fake faces from a given image.

Project Implementation Method

This is indeed a very interesting project but requires in depth study of deep learning, neural networks.

The following links may help you in better understanding:

Functional Requirements:

The following are the functional requirements of the project:

The tool based application/software must download the given Dataset that contains the database of real and fake images.

The system must be any CNN model that contains hidden layers for fake face detection.

Whenever, any face is given as an input into the detection system, it identifies as real or fake as output.

The system must be able to detect the fake faces generated by any of the android apps like FaceApp, FaceSwap, Wombo etc.

Tools:

Python (programming language)

Keras (API)

Tensorflow (open source software library for machine learning)

Jupyter Notebook (open source web application)

Matplotlib (library)

Numpy (library for the python)

Benefits of the Project

Nowadays social media is spreading like an odor. As everything has its advantages and also disadvantages. Making face fake on social media is a big problem for everyone mostly politicians, and other respectable people who are facing this problem. Now almost everyone is using this trend on social media and making fun of others. We made a web-based app in which we can detect any video or image and check whether it is real or not. Fake face detection project can be very helpful for every social media user. We have used CNN in the backend of this project. In this project , the deep machine learning technique is implemented as a detection technique for deepfake or manuplated images. The method works faster in execution and the detection of fake image and real image is very effective. Deepfake face image manipulations are analyzed using AI and deep machine learning model and it has also produced high level of accuracy. It helps in detecting the fake face present in an image which in turn could prevent the individuals from being defamed unknowingly. For future work, it may be extended up to various classifiers and use of different distance metric measures for detecting the deepfake face image.

Technical Details of Final Deliverable

Going digital has its own advantages and disadvantages in today’s modern time. It makes everything easy as well as feasible. Following the same paradigm, we felt the need to make the lives of peasants as well as common person practicable but keeping in mind the simplicity of use. The simplistic approach followed in our software will enable everybody to detect any fake faces or manuplated faces present in an image . Without getting stuck in the predicament of worries.

THECNICAL FEASIBILITY: The fake detection strategy is divided into various parts: Faces in Photos, Cycle of Programmed Face Acknowledgment, Face Detection Undertaking, Face Acknowledgment Errands, and Profound Learning for Face Acknowledgment.

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Telecommunication Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Decent Work and Economic GrowthRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	10000
Fake Face detections	Miscellaneous	1	10000	10000