Electrocardiogram (ECG) paper records are used commonly for diagnosing heart abnormalities. The stored paper ECG records may be blurred or affected by noise. Enhancement of such blurred paper ECG records is done using a low-pass Wiener filter and background grid removal using adaptive thresholding, signal extraction, and parameter extraction. In this work, clinically important parameters such as heart rate, R-peak, RR-interval, and S-peak are extracted from the enhanced digitized ECG signal, and these extracted parameters are then compared with printed parameters on original paper ECG records. The average absolute error between extracted parameters and original paper ECG parameters is 0.02 with an average accuracy of 97.66%. The extracted digitized signal from stored ECG records may be useful for retrospective analysis of cardiac abnormalities, using automated diagnosis software.