Forensic sketch to real image

Registration ID: IJNRD_220585

Published ID: IJNRD2405388

DOI: Click Here to Get

Mr. Balram Tondare , Mr. Rohan Shirsat , Mr. Aditya Tiwari , Ms. Kalyani Kute

DCGAN, computer vision, CNN, Sketch to image, Image processing, Face Synthesis, Generative Adversarial Networks

In the realm of forensic investigations, the reliance on hand-drawn sketches or verbal descriptions to identify suspects or victims is well-established. However, these traditional methods often present challenges due to their inherent subjectivity and potential inaccuracies. Recognizing the critical importance of enhancing the accuracy and efficacy of forensic identification processes, our project delves into cutting-edge techniques, particularly leveraging Deep Convolutional Generative Adversarial Networks (DCGANs). Situated at the nexus of image processing, artificial intelligence, and machine learning, these advanced algorithms offer promising avenues for transforming forensic sketches into remarkably realistic images. Our project's primary objective is to develop a robust Forensic Sketch to Real Image Conversion System capable of generating highly authentic images from both hand-drawn and computer-generated forensic sketches. By harnessing the power of DCGANs, we aim to bridge the gap between the abstract representations provided by traditional forensic sketches and the detailed, lifelike images necessary for effective identification and investigation. This innovative system holds immense potential to revolutionize forensic practices, offering law enforcement agencies invaluable tools to aid in criminal investigations, locate missing persons, and address a myriad of forensic challenges. Beyond its immediate applications in law enforcement and forensic science, the Forensic Sketch to Real Image Conversion System represents a significant stride towards advancing the intersection of technology and justice. By providing law enforcement agencies with the means to generate highly accurate depictions of suspects or victims from rudimentary sketches, our project seeks to bolster investigative capabilities while ensuring fairness and accuracy in criminal proceedings. Moreover, the potential societal impact extends beyond law enforcement, offering hope and closure to families of missing persons and victims of crime through improved identification methods

Published Paper   E-Certificate

Mr. Balram Tondare, Mr. Rohan Shirsat, Mr. Aditya Tiwari , & Ms. Kalyani Kute (May-2024). Forensic sketch to real image . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), d785-d795. https://ijnrd.org/papers/IJNRD2405388.pdf

Volume 9 Issue 5, May-2024

Pages : d785-d795

Paper Reg. ID: IJNRD_220585

Published Paper Id: IJNRD2405388

Downloads: 000121978

Research Area: Computer Science & Technology 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405388.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405388

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

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

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