Head-up display(HUD), a primary cockpit display, helps in optimizing a pilot’s attention towards aircraft and outside events. Slight mismatch in the balance may cause missed events; this phenomenon is called attention tunneling and affects the situational awareness of the pilot. This work reports an intuitive approach to detect attention tunneling while use of HUD in aircrafts. Texture analysis of a composite HUD camera video provided three distinguishing parameters, viz., contrast, correlation, and homogeneity. These three texture parameters are used as inputs for a fuzzy inference-based assistive detection system which could be used for distinguishing tunneled and nontunneled HUD operation. Head-up display (HUD), a primary cockpit display, helps in optimizing a pilot’s attention towards aircraft and outside events. This phenomenon is called attention tunneling and affects the situational awareness of the pilot. This work reports an intuitive approach to detect attention tunneling while using the HUD in aircrafts. Texture analysis of a composite HUD camera video provided three distinguishing parameters, viz., Contrast, correlation, and homogeneity. These three texture parameters are used as inputs for a fuzzy inference-based assistive detection system which could be used for distinguishing tunneled and nontunneled HUD operation.