Abstract
Medical technology employs a range of different computational methods for analyzing noninvasive heart rate monitoring processes. During the heart rate monitoring process, accurate heart rate detection is difficult which is overcome by applying the effective image processing techniques. Thus, the present study offers a mobile application framework that uses video frames captured from mobile camera. These video frames are analyzed by Eulerian video magnification (EVM) with a region extraction technique for efficiently detecting and monitoring heart rates. Initially, EVM captures the feelings of the subject from a face visualization process. Then, temporal filtering and spatial decomposition methods are applied to reconstruct the video frames. Subtle changes in the face image are extracted from the video frames by applying an enhanced multi-scale segmentation technique. The segmented region from the face helps to identify the intensity level of the green channel feature, which differs from the normal red and blue channel features. This process identifies the hidden heart rate from the region extracted by the EVM visualization process. Finally, system efficiency is evaluated in terms of the estimated heart rate, actual heart rate, and heart rate accuracy. The mobile based video magnification analyzing process reduces mortality rate, and accurately examines heart rates.