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Text recognition from distorted or degraded images especially handwritten is a challenge in computing . The present research work on "Enhancement Of Degraded Text Images & Performance Comparison", is an excellent effort to enhance the degraded text images caused by poor scanning, historical papers, and other causes. This study will propose a technique for the enhancement of such a degraded text document images to improve their display quality characteristics by using thresh hold values as well as a comparison of performance among them. Images believed to be representative of the same symbol which occurs in different positions over an image source are clustered together. Using the symbols within a particular cluster, an average character image outline for that cluster of symbols is derived and thereafter used to refine the matching of symbols within the cluster and to determine a final representative symbol for that cluster. Thus the partially visible or distorted text can be recognized. The work will definitely prove a helping hand to young researchers for developing new ideas and algorithms to resolve the practical problems of text image degradation and their recovery.