Radha, V2017-03-312017-03-312010https://ir.avinuty.ac.in/handle/avu/2404Texture analysis is an important approach in textile quality control. The investment in automated unit is more economical when reduction in labor cost and associated benefits are considered. Preprocessing in textile image is a crucial initial step before texture analysis is performed. Many preprocessing methods are available in the literature. Datasets are limited by laboratory constraints so that the need is for guidelines on quality and robustness, to proceed experimentation while image are yet restricted. In this paper, the performance of four preprocessing methods are compared namely Contrast adjustment. Intensity adjustment. Histogram equalization, Binarization and Morphological operation. The performances of these methods are evaluated using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).