Towards the automatic detection of hand fingertips and phalanges in thermal images

Abstract

Manual analysis of thermal images and definition of regions of interest (ROI) of hands is a tedious and time-consuming task. Towards the automatic detection of anatomical thermal ROIs, an algorithm to automatically detect fingertips and phalanges were developed, using MATLAB®. Two strategies for fingertips detection were applied. The two algorithms were developed using 48 hand thermal images (size 320 × 240) as a training set, while 12 integrated the test set. The algorithms’ evaluation metric assesses the hand binarization and edge extraction, as well as the fingertip and phalanges detection. This evaluation metric showed a hit score of 70.2% for the first approach and 88.6% for the second method. The first approach shows a reasonable relationship between the average temperature of the detected phalanges and the manual marked phalanges (R2 = 0.6477), while the second approach presents a much strongest linear correlation (R2 = 0.9551), where the variables are highly associated, proving its efficiency. Future work includes improving the algorithm by using a larger training set.