AN IMPROVED IMAGE COMPRESSION USING CURVELET TRANSFORM IN IRIS IMAGES FOR AUTHENTICATION

Methodologies for visually lossless compression of monochrome stereoscopic 3D images are measured for quantization distortion in JPEG2000. These thresholds are found to be functions of not only spatial frequency, but also of wavelet coefficient variance, as well as the gray level in both the left and right images. The left image and right image of a stereo pair are then compressed jointly using the visibility thresholds obtained from this model to ensure that quantization errors in each image are imperceptible to both eyes but can't use this model for authentication purpose. In this proposed system the new method of Curvelet Transform in blend with Lifting Scheme and Huffman coding are used to compress iris images for secure authentication. In different types of wavelet transforms, the C u r v e l e t transform provides better results for the curvy portions of iris images. Along with Curvelet transform, Lifting Wavelet transform is applied to the co-efficient of the Curvelet transformed image which will provide the high detailed image. Keywords - Authentication, jpeg2000, Curvelet transform, lifting scheme, Huffman coding