• Vishwajeet N. Jadhav
• Rameshwar S. Kawitkar

The use of image normalization and SVD decomposition hash functions to generate a hash value for a digital image. This study proposes a sturdy hashing technique victimization scale-invariant feature rework (SIFT) options points and distinct rippling rework approximation coefficients for image authentication. Initially, the invariant feature points ar computed victimization SIFT from the L∗ element of L∗a∗b∗ color image. Next, n distinct SIFT feature points ar utilised to extract image content from the L∗ element. Then, DWT is applied to extracted content so as to work out approximation coefficients. Finally, the approximation coefficients ar normalized to make a binary hash. Experimental results show that the projected technique is strong to varied content-preserving operations like compression, scaling, and filtering, additive noise, brightness, and distinction adjustment. Additionally, the performance of the projected technique is compared to existing ways employing a receiver operative characteristics curve. The comparison results show that the projected technique performs higher than the prevailing ways.

SVD and DWT for image hashing

"Survey on Image hashing using DWT and SVD and identification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.17-19, June 2019, Available :http://www.jetir.org/papers/JETIR1906Z03.pdf

"Survey on Image hashing using DWT and SVD and identification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp17-19, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Z03.pdf