Analysis and modeling of alcohol intoxication from IR images based on multiregional image segmentation and correlation with breath analysis

Alcohol intoxication is an important procedure which is related to all social areas. There are commonly used standards like are the blood analysis or breath analysis. Although such methods are commonly used and give satisfactory results, there are also certain drawbacks. For instance it is direct contact and awareness of the tested person. One challenging direction of the alcohol assessment is the temperature effect whilst drinking, thus temperature variations may be reliable indicators of the current alcohol state. The paper deals with a comparative analysis of three multiregional segmentation methods with target of building of a mathematical model reflecting the facial areas well reflecting the dynamical process of the alcohol drinking. By such modelling we can make a predictor of the alcohol state based on the facial temperature effect. We have specified two significant features: nose and forehead areas where the temperature variations are well observable. Eventually, we have done a verification analysis between individual dynamical models and breath analysis on the base of the Pearson correlation coefficient. Correlation gives relatively strong dependence, when we consider a fact that some persons have stronger inclination to the alcohol which may negatively influence the IR records and the segmentation results as well.