The Application Of Spectrogram Image Processing In The Bat"Dialect" Signal Analysis

Language is not only an important bridge of human communication, but also animportant communicate tool to bat. Different countries and regions of the language isdifferent, we call it dialect, however, the same as the bat community. The sound stylesof different populations and geographical bat are different. The key of my paper isabout the research of the bat “dialect” we take the greater horseshoe bat as an example,and distinguish between the different types of sound signals so that we simplyunderstand the semantics of the bat.The greater horseshoe bat sound samples are divided into five categories,provided by the College of Life Sciences, and classify them, respectively, AFM,BNBs, DFM, SFM and UFM, each class represents the same kind of meaning, and thesound samples are in different regions from China. In this paper, we analyze the soundof bat based on the previous studies on the human speech, and put forward the bat"dialects" signal spectrogram method for image processing. According to the inherentcharacteristics of spectrogram, we do the feature extraction of the greater horseshoebat five sound types by applying the mathematical morphology image processingtechnology, combining the speech recognition technology and image processingtechnology, so as to distinguish “dialect” purposes.We study on the algorithm by introducing the MATLAB7.0software. Theprocess is as follows. The algorithm firstly introduces the Cool Edit Pro2.1softwarefor recorded “dialect" bat signal preprocessing, unifies the quantitative standard,achieves the resulting spectrogram image by capture software. Secondly, process thebat "dialect" spectrogram by applying the histogram image processing technology.Thirdly, do the binarization, morphological filtering and skeleton processing by usingthe mathematical morphological image processing technology. Finally, do the angleprocessing about the results of the bat "dialect" signals spectrogram. To test theexperimental results and determine rationality, the BP neural network is detected.