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This paper shows how dynamic heart rate measurements that are typically obtained from sensors mounted near to the heart can also be obtained from video sequences. In this study, two experiments are carried out where a video camera captures the facial images of the seven subjects. The first experiment involves the measurement of subjects' increasing heart rates (79 to 150 beats per minute (BPM)) while cycling whereas the second involves falling heart beats (153 to 88 BPM). In this study, independent component analysis (ICA) is combined with mutual information to ensure accuracy is not compromised in the use of short video duration. While both experiments are going on measures of heartbeat using the Polar heart rate monitor is also taken to compare with the findings of the proposed method. Overall experimental results show the proposed method can be used to measure dynamic heart rates where the root mean square error (RMSE) and the correlation coefficient are 1.88 BPM and 0.99 respectively. for measuring R-R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system," Eur. J. Appl. Physiol. 109(4), 779-786 (2010). 6. M. Garbey, N. Sun, A. Merla, and I. Pavlidis, "Contact-free measurement of cardiac pulse based on the analysis of thermal imagery," IEEE Trans.

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A difficult challenge in obtaining clear images in underwater environment is because of poor visibility of objects due to light attenuation and color distortion. A solution to this is to do some form of enhancement of the image that eventually leads to better visualization. This paper presents a comparative analysis of three different enhancements techniques: contrast stretching (CS), histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE) in the RGB and HSV color spaces for underwater images. Besides visual inspection, two different quantitative performance evaluation metrics, namely the Edge Contrast (EC) and BRISQUE, are used to assess the quality of the enhanced underwater images. Experimental results show that the CLAHE method performs better than CS and HE methods in both color spaces from the quality scores obtained in the EC as well as with the subjective evaluations.

In this paper, facial images from various video sequences are used to obtain a heart rate reading. In this study, a video camera is used to capture the facial images of eight subjects whose heart rates vary dynamically, between 81 and 153 BPM. Principal component analysis (PCA) is used to recover the blood volume pulses (BVP) which can be used for the heart rate estimation. An important consideration for accuracy of the dynamic heart rate estimation is to determine the shortest video duration that realizes it. This video duration is chosen when the six principal components (PC) are least correlated amongst them. When this is achieved, the first PC is used to obtain the heart rate. The results obtained from the proposed method are compared to the readings obtained from the Polar heart rate monitor. Experimental results show the proposed method is able to estimate the dynamic heart rate readings using less computational requirements when compared to the existing method. The mean absolute error and the standard deviation of the absolute errors between experimental readings and actual readings are 2.18 BPM and 1.71 BPM respectively.