Face Recognition On Principal Component Analysis

ABSTRACT Facial recognition plays a significant role in different applications such as human computer communication, video surveillance, face tracking and face recognition. Efficient face recognition algorithm is required to accomplish such task. Face recognition is one of the most active research areas in computer vision and pattern recognition with practical applications. In present networked world, the need to conserve the security of information is becoming both increasingly significant and increasingly hard. In recent time, there has been an increasing spike in crimes related to identity theft and other forms fraudulent activities over the internet; examples are: credit card fraud, hacking, etc. The existing face recognition systems are able to circumvent the problem of identity theft but are not scalable and can’t run on low memory devices. In this project, a face recognition system that is scalable for mobile based identity sensitive applications like internet banking is developed. To achieve the scalability, the principal component analysis (PCA) is employed to reduce the dimensions of features of a face, which usually exist in high dimensions. Then, these features are classified using haar cascade classifier to achieve face recognition of a given person.

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APA

Mohammed, I (2021). Face Recognition On Principal Component Analysis. Afribary. Retrieved from https://tracking.afribary.com/works/face-recognition-on-principal-component-analysis

MLA 8th

Mohammed, IBRAHIM "Face Recognition On Principal Component Analysis" Afribary. Afribary, 23 Apr. 2021, https://tracking.afribary.com/works/face-recognition-on-principal-component-analysis. Accessed 14 Nov. 2024.

MLA7

Mohammed, IBRAHIM . "Face Recognition On Principal Component Analysis". Afribary, Afribary, 23 Apr. 2021. Web. 14 Nov. 2024. < https://tracking.afribary.com/works/face-recognition-on-principal-component-analysis >.

Chicago

Mohammed, IBRAHIM . "Face Recognition On Principal Component Analysis" Afribary (2021). Accessed November 14, 2024. https://tracking.afribary.com/works/face-recognition-on-principal-component-analysis

Document Details
IBRAHIM Ibrahim Mohammed Field: Computer Science Type: Thesis 58 PAGES (6240 WORDS) (pdf)