An electrocardiogram (ECG) is an important and commonly used diagnostic aid in cardiovascular disease diagnosis. Physicians routinely perform diagnosis by a simple visual examination of ECG waveform shapes. In this paper, we address the problem of shape-based retrieval of ECG recordings, both digital and scanned from paper, to infer similarity in diagnosed diseases. Specifically, we use the knowledge of ECG recording structure to segment and extract curves representing various recording channels from ECG images. We then present a method of capturing the perceptual shape similarity of ECG waveforms by combining shape matching with dynamic time warping. The shape similarity of each recording channel is combined to develop an overall shape similarity measure between ECG recordings. Results are presented that demonstrate the method on shape-based matching of various cardiovascular diseases.