• Mohamed Alkib Javed
• Prince Kumar
• Syed Abdul Mannan
• Yash Badia
• Mr. Yadhukrishna MR

Sparse-representation based classification (SRC) has been appearing great execution for face recognition as of late. Be that as it may, SRC isn't great at face recognition with low-quality pictures (e.g., camouflaged, undermined, impeded, etc.) which regularly show up in handy applications. To take care of the issue, In Face Recognition using low quality images(FRULQI), we propose a novel SRC based strategy for face recognition with low-quality images. In SLCR, we use low-position grid recuperation on the preparation dataset to acquire low-position segments and non-low-position segments, which are utilized to develop the word reference. The new dictionary is equipped for depicting facial element better, particularly for low- quality face tests. Besides, the base class-wise recreation remaining is utilized as the acknowledgment rule, prompting a generous enhancement for the proposed SLCR's execution. Broad trials on benchmark face databases exhibit that the proposed technique is reliably better than other sparse-representation based methodologies for face acknowledgment with low-quality pictures.

Face recognition, sparse-representation based classification , low quality images.

"FACE RECOGNITION USING LOW QUALITY IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.129-132, May-2019, Available :http://www.jetir.org/papers/JETIRCD06021.pdf

"FACE RECOGNITION USING LOW QUALITY IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp129-132, May-2019, Available at : http://www.jetir.org/papers/JETIRCD06021.pdf