Facial Recognition for Locating Missing Child Using CNN Algorithm

In India, countless children are reported missing every year, with a significant percentage remaining untraced due to challenges in identification and limited resources. This project introduces a deep learning-based facial recognition system to efficiently and accurately assist in locating missing children. The system enables the public to upload photographs of suspected missing children via a shared platform, along with details such as location and remarks. These images are automatically compared against a database of registered photos of missing children. The proposed solution utilizes Convolutional Neural Networks (CNN) for feature extraction and Support Vector Machines (SVM) for classification. It addresses common challenges in facial recognition, such as variations in noise, lighting, occlusion, image pose, and the natural aging of children. By integrating CNN and SVM, the system ensures improved accuracy and robustness over traditional methods. This initiative not only supports law enforcement in their efforts to locate missing children but also fosters community involvement through an interactive platform. With real-time matching capabilities and high reliability, the system significantly enhances efforts to reunite missing children with their families, enabling a faster and more effective recovery process.