MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641108343 A) filed by Rns Institute Of Technology; Nithin B; Naga Likith M V; Manoj Gowda N; Prajwal J Athreyas; Pranjal Sharma; Bharath M; and Dr. Chandana C on September 09, 2026, for An Ai-Based Face Recognition System Using Machine Learning Techniques.
Inventors include Nithin B; Naga Likith M V; Manoj Gowda N; Prajwal J Athreyas; Pranjal Sharma; Bharath M; and Dr. Chandana C.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: Artificial Intelligence (AI) has become one of the most influential technologies in today's world, providing intelligent solutions to various real-life problems. Face recognition is one of the most widely used applications of AI and computer vision. It is a biometric technology that identifies or verifies a person by analyzing unique facial features. Due to its accuracy, speed, and convenience, face recognition systems are increasingly being used in security, attendance management, access control, surveillance systems, smartphones, and many other applications. The AI-Based Face Recognition System is designed to automatically detect and recognize human faces from images or live video streams. The system captures facial images using a camera and processes them using artificial intelligence and machine learning algorithms. The captured face is compared with a database of stored facial images to identify or verify the person's identity. This automated process eliminates the need for manual identification and improves efficiency and security. The system consists of several stages, including image acquisition, face detection, feature extraction, face matching, and recognition. Initially, the camera captures an image containing one or more faces. The face detection module identifies the location of faces in the image. After detection, important facial features are extracted and converted into numerical representations. These features are then compared with the stored facial data in the database. If a match is found, the identity of the person is displayed; otherwise, the person is marked as unknown. Machine learning and deep learning techniques play a crucial role in improving the accuracy and reliability of face recognition systems. Algorithms such as Convolutional Neural Networks (CNNs) can learn complex facial patterns and distinguish between different individuals even under varying lighting conditions, facial expressions, and viewing angles. This enables the system to perform recognition with high accuracy and minimal human intervention. The proposed system offers several advantages, including fast recognition speed, improved security, reduced human effort, and enhanced user convenience. It can be effectively used in educational institutions for attendance monitoring, organizations for employee verification, residential areas for access control, and public places for surveillance and security purposes. In conclusion, the AI-Based Face Recognition System provides an intelligent, efficient, and reliable solution for personal identification and authentication. By utilizing artificial intelligence and machine learning technologies, the system enhances security while simplifying identification processes across various applications and environments.
Disclaimer: Curated by HT Syndication.
