Comparison of two methods for detection of North Atlantic Right Whale upcalls

In this paper, a study is carried out for detecting North Atlantic Right Whale upcalls with measurements from passive acoustic monitoring devices. Preprocessed spectrograms of upcalls are subjected to two different tasks, one of which is based on extraction of time-frequency features from upcall contours, and the other that employs a Local Binary Pattern operator to extract salient texture features of the upcalls. Then several classifiers are used to evaluate the effectiveness of both the contour-based and texture-based features for upcall detection. Detection results reveal that popular classifiers such as Linear Discriminant Analysis, Support Vector Machine, and TreeBagger can achieve high detection rates. Furthermore, using LBP features for call detection shows improved accuracy of about 3% to 4% over time-frequency features when an identical classifier is used.