Thermographic imaging has been shown an efficacious method for analysis of gait abnormality in canines. A total of 168 images were used from multiple views of canine’s legs. An algorithm was developed for the automatic mask creation of these thermographic canine leg images to locate important gait related areas. The algorithm is compared with other segmentation and enhancement combinations using the CVIPtools Algorithm Testing and Analysis Tool (ATAT). The ATAT software was able to identify an algorithm with an average 88.4% success rate using the Dice coefficient and Jaccard Index as the main error measurements.
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