Audio segmentation is one of the stages in audio processing chain whose accuracy plays a primary role in the final performance of the audio recognition and processing tasks. This paper presents an analysis of auditory features for audio segmentation. A set of features is derived from a time-frequency representation of an input signal and has been calculated based on properties of human auditory system. An analysis of several sets of audio features efficiency for BIC-based audio segmentation has been performed. The obtained results show that auditory features derived from different frequency scales are competitive to the widely used MFCC feature in terms of accuracy and the number of detected points.