Paper Title

A Review on Fake Image Detection Using Machine Learning

Article Identifiers

Registration ID: IJNRD_191816

Published ID: IJNRD2304413

DOI: Click Here to Get

Authors

Sahil Meshram , Vaishali Gedam , Shrinivas chinchanikar , Yash Lad , Ganesh pandey, Punam Bhandarkar

Keywords

Biometry, Identity, Recognition, Detection, Fake face.

Abstract

Nowadays biometric systems are useful in recognizing a person’s identity, but criminals change their appearance in behaviour and psychological to deceive recognition system. To overcome this problem we are using a new technique called Deep Texture Features extraction from images and then building train machine learning model using CNN (Convolution Neural Networks) algorithm. This technique refers as LBPNet or NLBPNet as this technique is heavily dependent on features extraction using LBP (Local Binary Pattern) algorithm. In this project, we are designing LBP Based machine learning Convolution Neural Network called LBPNET to detect fake face images. Here first we will extract LBP from images and then train LBP descriptor images with Convolution Neural Network to generate a training model. Whenever we upload a new test image then that test image will be applied to the training model to detect whether the test image contains a fake image or a non-fake image. Below we can see some details on LBP.

How To Cite

"A Review on Fake Image Detection Using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 4, page no.e78-e83, April-2023, Available :https://ijnrd.org/papers/IJNRD2304413.pdf

Issue

Volume 8 Issue 4, April-2023

Pages : e78-e83

Other Publication Details

Paper Reg. ID: IJNRD_191816

Published Paper Id: IJNRD2304413

Downloads: 000121167

Research Area: Computer Science & Technology 

Country: Nagpur, maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304413.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304413

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

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Frequency: Monthly (12 issue Annually).

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