摘要：Lung sounds have information to seek abnormalities in the lung. With digital signal processing,
the information in the lung sounds is extracted as the features in lung sound classification. In
this paper, texture analysis was used to measure the complexity of lung sound as a feature in
lung sound classification. Grey-Level Difference (GLD) method was performed on lung sounds
with a number of different scales. Multi-scale GLD has produced accuracy up to 90.12% for five
classes of data. Further, gradient entropy individually provided the highest accuracy up to
91.36% for the distance D = 20 and a scale of 1-10.
