Face Detection using Machine Learning Method |
Author(s): |
| Rupika , SAT KABIR INSTITUTE OF TECHNOLOGY AND MANAGEMENT; Shalini, SAT KABIR INSTITUTE OF TECHNOLOGY AND MANAGEMENT; Kirti Bhatia, SAT KABIR INSTITUTE OF TECHNOLOGY AND MANAGEMENT |
Keywords: |
| Face Recognition, KNN, PCA, Eigen Vectors |
Abstract |
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Face Recognition is an exciting task in the field of machine learning. Various techniques and methods have been used to solve the problem of face recognition. In this paper, we have shown that how K Nearest Neighbors algorithm along with Principal Component Analysis can be used to recognize a face efficiently. K nearest neighbor algorithm is a non parametric learning algorithm that works on target values of K nearest data points of the query point and finalize the value of the query point. PCA uses the concept of Eigen vectors. An Eigen vector represents an image. PCA finds K Eigen vectors corresponds to K higher Eigen values. So PCA algorithm is an efficient method for feature extraction in face recognition. Implementation is done using python programming language. This paper shows the effect of combination of above mentioned technologies and their edge cutting results. |
Other Details |
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Paper ID: IJSRDV7I40017 Published in: Volume : 7, Issue : 4 Publication Date: 01/07/2019 Page(s): 63-65 |
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