Sound source localization is a need for robotic systems interacting with acoustically-active environments. In this domain, numerous binaural localization studies have been conducted within the last few decades. This paper provides an overview of a number of binaural localization cue extraction techniques. These are carefully addressed and applied on a simulated binaural database. Cues are evaluated in azimuth estimation and their discriminatory effectiveness is studied as a function of the reverberation time with statistical data analysis techniques. Results show that big differences exist between the discriminatory abilities of multiple types of cue extraction methods. Thus a careful cue selection must be performed before establishing a sound localization system.