Quantitative Measurements of Forward Flapping Flight Using Image Processing

A method for automatically calculating the flight kinematics of a flapping bird flying on a relatively dense background environment was developed. The algorithm is able to calculate the bird’s flapping frequency, wingbeat phase, forward velocity, and forward acceleration with good accuracy with the use of only one camera. Image processing was used for extracting the bird’s silhouette from the background. An image matching algorithm, which made use of the Kullback–Leibler divergence, was used for matching a unique template frame to similar frames of the flight. The algorithm was tested on three full flights of one bird. The algorithm was able to detect similar wingbeat phases with 100% detection accuracy for every data set, giving good accuracy for the flight kinematics. Keywords—image processing, KL divergence, bird flight,