Psoriasis is a skin disorder which typically consists of red plaques covered by silvery-white scales. The extent of the psoriasis lesion has to be assessed in determining treatment efficacy. PASI (Psoriasis Area and Severity Index) is gold standard for assessing the extent of psoriasis lesion. Scaliness is one of the parameters of PASI scoring. However, determining this parameter is found to be subjective as there are inter and intra observer variations. In this work, we develop an image processing method for PASI scaliness scoring. The method converts the depth information of the 3D lesion images (surfaces) into 2D grayscale images. Gray Level Co-occurrence Matrix (GLCM) is used to analyze the 2D images. From 14 patients with scaliness scores 1, 2 and 3, results show that the method has the potential to determine PASI scaliness score. ©2007 IEEE.