1.
Nimisha Rajeev P.
– Comp. Science And Engineering, Sree Narayana Guru College Of Engg. And Tech., Payyanur, Kerala
2.
Anima M.
– Comp. Science And Engineering, Sree Narayana Guru College Of Engg. And Tech., Payyanur, Kerala
3.
Heera Mohan K. V.
– Comp. Science And Engineering, Sree Narayana Guru College Of Engg. And Tech., Payyanur, Kerala
4.
Pranav P. V. And Swetha Pai
– Comp. Science And Engineering, Sree Narayana Guru College Of Engg. And Tech., Payyanur, Kerala
Abstract
Image processing is a wide area which has attained attention over the last few decades. Multiple faces can be detected using Image Processing Techniques. Various algorithms are utilised to develop software and hardware that recognises the human face. The algorithm will compare the various pictures to pre-defined or learnt images, as well as real video images. Security and surveillance, authentication/access control systems, digital healthcare, photo retrieval, and other applications have all benefited from its use. This approaches needs maximum information, in certain conditions it is difficult to gain those informations such as small face detection, night person identification, partial face recognition, occlusion and so-forth. Opportunities and problems are inextricably linked. Growing business interest in face recognition is good, but it also proves to be a difficult undertaking when it comes to the difficulties that have plagued its quality of delivery. This paper gives a high-level overview of general solutions to these problems.
Keywords Artificial Intelligence (AI), Image processing, IoT, Machine learning.
