Iris Image Processing in Compressive Sensing Scenario
This paper observes the application of the Compressive Sensing in reconstruction of the under-sampled iris images. Iris recognition represents form of biometric identification whose usage in real applications is growing. Compressive Sensing represents a novel form of sparse signal acquisition and recovering when small amount of data is a available. Different sparsity domains are considered and compared using various number of available image pixels. The theory is verified on iris images.
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