Automated Thermal Image Processing for Detection and Classification of Birds and Bats - FY2012 Annual Report

Duberstein, Corey A. ; Matzner, Shari ; Cullinan, Valerie I. ; Virden, Daniel J. ; Myers, Joshua R. ; Maxwell, Adam R.

Pacific Northwest National Laboratory (U.S.)

关键词: Wildlife;    Infrared;    Bats;    Risk Assessment;    Wind Energy;   

DOI  :  10.2172/1076723
RP-ID  :  PNNL-21911
RP-ID  :  AC05-76RL01830
RP-ID  :  1076723

美国|英语

来源: UNT Digital Library

【 摘 要 】

Surveying wildlife at risk from offshore wind energy development is difficult and expensive. Infrared video can be used to record birds and bats that pass through the camera view, but it is also time consuming and expensive to review video and determine what was recorded. We proposed to conduct algorithm and software development to identify and to differentiate thermally detected targets of interest that would allow automated processing of thermal image data to enumerate birds, bats, and insects. During FY2012 we developed computer code within MATLAB to identify objects recorded in video and extract attribute information that describes the objects recorded. We tested the efficiency of track identification using observer-based counts of tracks within segments of sample video. We examined object attributes, modeled the effects of random variability on attributes, and produced data smoothing techniques to limit random variation within attribute data. We also began drafting and testing methodology to identify objects recorded on video. We also recorded approximately 10 hours of infrared video of various marine birds, passerine birds, and bats near the Pacific Northwest National Laboratory (PNNL) Marine Sciences Laboratory (MSL) at Sequim, Washington. A total of 6 hours of bird video was captured overlooking Sequim Bay over a series of weeks. An additional 2 hours of video of birds was also captured during two weeks overlooking Dungeness Bay within the Strait of Juan de Fuca. Bats and passerine birds (swallows) were also recorded at dusk on the MSL campus during nine evenings. An observer noted the identity of objects viewed through the camera concurrently with recording. These video files will provide the information necessary to produce and test software developed during FY2013. The annotation will also form the basis for creation of a method to reliably identify recorded objects.