Abstract—Non Uniform Illumination in an image often leads to diminished structures and inhomogeneous intensities of the image due to different texture of the object surface and shadows cast from different light source directions. This effect is adverse in case of biological images. Techniques such as segmentation, edge detection and contrast or brightness enhancement using Histogram Equalization could not differentiate between some of the particles and their background or neighbouring pixels. This paper is aimed to remove these problems in microscopic image processing by removing the problem of non-uniform background illumination from the image using Morphological Opening, Adaptive Histogram Equalization and Edge detection techniques for particle analysis , a comparative study have been shown and a new algorithm is proposed for removing the problem of non-uniform background illumination in biological images such as visualizing and estimation of growth of a fungus in a particular sample to transform the input image to its indexed form with maximum accuracy involving morphological openings and structuring element design using Morphological Opening
 

Index Terms—morphological opening, thinning, skeletonization, histogram equalization, thresholding, structuring element

Cite: Prabhdeep Singh and Vandana Chauhan, "Non Uniform Illumination Reduction Using Morphological Dilation and Erosion for Area Based Statistics Computation," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 6, No. 3, pp. 1-6, July 2017. DOI: 10.18178/ijeetc.6.3.1-6