Face Recognition System Using Haar Cascade and LBP Classifier

Facial recognition is becoming more and more in demand as technology advances. Among the several facial recognition algorithms that are available, the Linear Binary Pattern Classifier and the Haar cascade is used Due to the fact that they are complimentary methods that provide facial recognition with both speed and accuracy. The Haar Cascade and the LBP are the best techniques for classification. The Haar Cascade approach achieved 85 % overall accuracy and faster processing times; each image recognition took an average of 50 milliseconds. On the other hand, the LBP algorithm recorded an accuracy of 78 % with an average detection time of 70 milliseconds per image, and a significantly reduced false positive rate of 10 %, indicating higher resistance to changes in facial expression and occlusions. For this, the widely used OpenCV library is utilised. The proposed methodology makes use of the LBP classifier and the Haar cascade, two well-known classifiers. Integral pictures are used to quickly compute features in the Haar cascade classifier, which is well-known for its speed and effectiveness in real-time object recognition. Capable of classifying textures in digital pictures, the LBP classifier stores local texture information for reliable identification.