The purpose of this study was to enhance Windows user access security by developing a Multi-Feature Face Detection and Recognition focusing on laptop brands namely Asus, Lenovo and Toshiba which offers a Face Recognition feature. Emgu CV’s Haar-cascade and Eigenface Recognizer were used in detecting and recognizing faces while the blink detection algorithm was implemented to detect blinks. A biometrics test was conducted to measure the performance and accuracy of the proposed system. The researchers found that implementing blink detection on a face recognition access security helps in countering authentication and access bypass via photo of the authorized user. It is recommended to developers to consider image processing enhancements which deals with lighting and different environments and a camera calibration technique for a more reliable and faster image processing. Developing the system with other operating systems would also result to better functionality and effectiveness.