Face Recognition Challenges and Solutions using Machine Learning


  • Kavita Research Scholar, Department of Computer Science and Applications, M. D. University, Rohtak, Haryana, India
  • Rajender Singh Chhillar Professor, Department of Computer Science and Applications, M. D. University, Rohtak, Haryana, India


face detection, face recognition, illumination, occlusion


Face Recognition is an interesting real-time field of Computer Vision. After many efforts the research is still in development stage. Although recent developments in face recognition has been done but challenging also. Particularly, challenges come with: different positions of faces, illumination levels varied, blurred faces, post surgery faces. With the help of Face detection and face recognition; one can identify the right person from the captured face with a camera/video. The objective of the research is to consider the existing research in the area of face detection & face recognition & finding their limitation such as accuracy and performance. This paper presents the issues such as aging, illumination, occlusion, facial expressions, low resolution etc. This paper is a study of the techniques, tools and possible expected solutions to enhance the performance of the FR system.


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Face Recognition dimension measures




How to Cite

Kavita and R. S. . Chhillar, “Face Recognition Challenges and Solutions using Machine Learning”, Int J Intell Syst Appl Eng, vol. 10, no. 3, pp. 471–476, Sep. 2022.



Research Article