MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641051068 A) filed by Sathyabama Institute Of Science And Technology; Dr. V. R. Niveditha; Seesa. Vinay; Kowkuntla. Ruthwik Reddy; Manish. M; Michlin Archaya. M; Uhandara Devi N; and Tanikella Hari Gayatri, Chennai, Tamil Nadu, on April 22, for 'ai - assisted search for identifying missing persons.'
Inventor(s) include Sathyabama Institute Science And Technology; Dr. V. R. Niveditha; Seesa. Vinay; Kowkuntla. Ruthwik Reddy; Manish. M; Michlin Archaya. M; Uhandara Devi N; and Tanikella Hari Gayatri.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Missing person cases represent one of the most pressing humanitarian and law enforcement challenges of the modern era. Every year, thousands of individuals across the world including children, elderly persons, and vulnerable adults are reported missing due to a wide range of causes such as human trafficking, abductions, natural disasters, mental health crises, and voluntary disappearances. The traditional methods used by law enforcement agencies and non-governmental organizations (NGOs) for identifying missing individuals rely heavily on manual search processes, witness testimonies, static photographs, and paper-based record keeping. These conventional approaches are inherently slow, resource-intensive, and error-prone, especially when dealing with large-scale databases or poor-quality images captured under challenging conditions. This project presents an AI-Assisted Search System for Identifying Missing Persons, a robust and resource-efficient face recognition platform designed to significantly improve both the speed and accuracy of missing person identification. The system integrates well-established classical computer vision techniques with contemporary machine learning algorithms to deliver reliable recognition performance even on devices with limited computational resources, making it highly accessible to small police departments, NGOs, and community-led search organizations the foundation of the system lies OpenCV, a widely adopted open-source computer vision library. OpenCV is used for critical pre-processing tasks including image resizing, color space conversion (RGB to grayscale), contrast enhancement using histogram equalization, noise reduction through Gaussian blurring, and face detection using Haar Cascade classifiers and Deep Neural Network (DNN) modules. Following detection, Media Pipe Face Mesh is optionally integrated to perform precise facial landmark extraction, identifying up to 468 key points on the face, including the positions of the eyes, nose, mouth, and jawline contours. This landmark data is used to align and normalize detected faces before feature."
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