Fast implementation of the Niblack binarization algorithm for microscope image segmentation

Abstract

A fast way to implement the Niblack binarization algorithm is described. It uses not only the integral image for the local mean values calculation, but also the second order integral image for the local variance calculation. Following the proposed approach the time of segmentation has been significantly reduced providing the possibility of its use in practice. The generalization of integral image representation, called ‘k-order integral image’ could be used for fast calculation of higher order local statistics. An example of algorithm for the segmentation of cells and Chlamydial inclusions on microscope images, containing the steps for color deconvolution and fast adaptive local binarization is presented.