Authors: Pilli Satya Sri, M Sujana Priya Darshini
Abstract: Finding missing persons is a challenging task that often requires significant time, manual investigation, and coordination between authorities and the public. This paper presents an AI-assisted missing-person identification system that uses face recognition and machine learning to support the search and identification process. The proposed system allows authorized personnel to register missing-person cases by storing details such as name, age, contact information, location, and photographs in a centralized database. The system also provides a user interface through which the public can submit photographs of unidentified or potentially missing persons along with relevant information. The submitted images are processed and compared with the registered missing-person photographs using facial feature matching techniques. When a suitable match is identified, the system provides the corresponding case information and supports notification to the concerned user or authority. The application is implemented using Python, PyQt5, PostgreSQL, and machine learning-based face recognition techniques, providing an integrated platform for case management, image matching, and search assistance. The proposed system aims to reduce manual effort, improve the speed of image-based identification, and support police and public participation in locating missing persons.
