Real-Time Criminal Face Identification Based on Haar-Cascade and Lbph, with Automatic Message Delivery to Whatsapp

Using a machine learning approach, a number of algorithms for automatic face identification of offenders depending on specified goals have recently been developed. Various algorithm has been proposed for face detection such as Eigenface using PCA (Principal Compound Analysis), Fisherface using Linear Discriminative method, Local Binary Pattern, active appearance, 3D shape models. For face recognition, the Local Binary Pattern Histogram technique is employed in this research. The data augmentation is also done, which provides the better performance in training. Haar cascade is used for extracting the features like eyes, nose length, cheek, lips, etc. Initially using the web camera, the individual persons cropped grayscale images are collected as database. Then the classifier trains the images, the data augmentation is used when datasets of the person is not enough. Using the web camera, the images are detected and recognized the person and that information a message will be sent to WhatsApp.