The development of several sectors and organizations has continually required the incorporation of some security measures into their systems to safeguard all resources concerned. Identity verification has become one of the means of providing access to some organizational facilities. For the need for a more reliable and effective system for verifying individuals' identity, several identity recognition systems have been discovered, one of which is Haar Cascade Classifier which has been extensively used for image detection and recognition purposes. This paper aims to discuss several concepts of Haar Cascade. This paper covers what Haar cascade is, its application, its implementation, and the pros and cons of using Haar Cascade Classifiers. The implementation to be carried out in this paper will focus on facial detection and recognition to enable us to understand the complexity in the process of image detection and recognition and to also understand the positive and negative contributions of different factors be it lighting variation, environmental conditions, and different facial expressions. This paper will as well evaluate the performance of the Haar Cascade classifier to detect unique facial characteristics and compare the results at every level of implementation to see how reliable and accountable the Haar Cascade is when it comes to the need for detecting and recognizing faces in images. OpenCV and Python programming language will be used to develop possible algorithms required in this paper for the final result to be judged upon.

In this research paper, existing face detection and recognition have been looked into, and performance evaluation of Haar Cascade through the implementation of face detection and face recognition algorithms through the use of OpenCV. This paper brings readers to an understanding of different face detection algorithms.