Leukemia Cell Recognition with Zernike Moments of Holographic Images

In this paper, we use the digital holographic method to classify-recognize an unknown leukemia cell. This is a non-invasive method to microscopy biology samples in order to recognize them. We generate the hologram from the 2D digital images of blood cells and make the reconstruction of leukemia cell through a computer simulation. We utilize approximate Fresnel digital holography in order to simulate optical diffraction patterns of hologram. A feature selection process is done on a computer reconstructed holographic image where we use the Zernike moments as the features of digital image. We take advantage of the rotation invariant property of the Zernike moments in the recognition of leukemia cell due to its unknown rotational direction. We compute the Zernike moments from scale and translation invariant geometric moments. In order to classify the leukemia cell, we use the minimum mean distance and the K-nearest neighbor methods using the invariant features