Chronic Kidney Disease of unknown aetiology (CKDu) is a prevalent disease in the North Central Province of Sri Lanka. Towards the latter stages of the disease, kidney function fails by 80%. During the initial stages of CKDu, interstitial fibrosis is formed and grows as the disease progresses. The cause of the disease remains elusive and early detection is vital to arrest the progressive decline of kidney function. The objective of this study is to construct a computer program to perform texture analysis on ultrasound kidney images and extract various features that can be used to distinguish between normal and diseased kidney patients. The computer program was developed using MATLAB and a user interface was created to perform mathematical operations such as: Fourier analysis to extract Root Mean Square and First Moment values and Grey Level Co-occurrence Matrix (GLCM) to extract Homogeneity and Sum Average values. A sample of ultrasound images were taken from 32 patients. Region of interest (ROI) selection was performed on entire kidney, cortex region and white (renal medulla or renal sinus) region separately. Among these methods Root Mean Square values over the entire kidney (p=0.03) and cortex region (p=0.0049) gave significant results in distinguishing between normal and diseased kidneys.