Paper Title

Enhancing Visual Media Engagement: Real-Time Cartoonization and Feature Enhancement of Photos and Videos

Article Identifiers

Registration ID: IJNRD_224538

Published ID: IJNRD2407030

DOI: Click Here to Get

Authors

RAGANNAGARI VENKATA SREEVIDYA , P Satish Kumar , Yeddula sreelatha

Keywords

Visual Media Engagement, Real-Time Cartoonization, Feature Enhancement of Photos and Videos

Abstract

The demand for transforming real-life photographs and videos into stylized cartoon versions has surged with the rise of social media and digital content creation. This project proposes an innovative approach using Generative Adversarial Networks (GANs) to achieve real-time cartoonization, aimed at enhancing user engagement and creativity across digital platforms. The project leverages advanced machine learning techniques implemented through the Python OpenCV package. Initially, the methodology involves preprocessing steps to optimize input media quality. This includes upsampling to enhance resolution and denoising to reduce visual artifacts, ensuring high-quality transformations. Subsequently, GAN-based models are employed for cartoonization, trained on a diverse dataset encompassing various artistic styles and preferences. The models generate cartoonized versions of photographs and videos with real-time processing capabilities, catering to dynamic digital content needs. Beyond cartoonization, the project integrates feature enhancement functionalities. Filters are applied to stylize images according to user preferences, enhancing visual appeal and artistic expression. This iterative process allows users to customize and refine cartoonized outputs, fostering creativity and personalization in digital content creation. Moreover, the project includes tools for converting cartoonized videos into GIFs, facilitating easy sharing and dissemination on social media platforms. Central to the project is the development of a user-friendly image hub. This interface serves as a centralized platform where users can upload, process, and download their transformed media seamlessly. Intuitive controls enable users to adjust cartoonization parameters, explore different styles, and preview results in real-time. The interface design prioritizes accessibility and usability, accommodating both casual users and digital content creators seeking innovative ways to engage audiences. The proposed method holds broad applications across creative industries such as comic book production, anime creation, and digital storytelling. By democratizing the process of cartoonization and feature enhancement, the project empowers users to explore new avenues of visual expression and storytelling. It bridges traditional media with digital innovation, offering versatile tools to amplify visual content impact and audience engagement in the digital era. In conclusion, this project represents a significant advancement in real-time cartoonization and feature enhancement of photographs and videos using GANs and image processing techniques. By combining technical sophistication with user-centric design, the project aims to redefine digital media engagement and creativity. Through accessible tools and customizable functionalities, it seeks to inspire and empower users to unleash their artistic potential, reshaping digital storytelling and visual communication landscapes.

How To Cite

"Enhancing Visual Media Engagement: Real-Time Cartoonization and Feature Enhancement of Photos and Videos", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 7, page no.a287-a296, July-2024, Available :https://ijnrd.org/papers/IJNRD2407030.pdf

Issue

Volume 9 Issue 7, July-2024

Pages : a287-a296

Other Publication Details

Paper Reg. ID: IJNRD_224538

Published Paper Id: IJNRD2407030

Downloads: 000121160

Research Area: Computer Engineering 

Country: Cuddapah, Andra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2407030.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407030

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

Publisher: IJNRD (IJ Publication) Janvi Wave

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Call For Paper

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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Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

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

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area