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The producers need to increase productivity and process economics leads to the use of technologies directed to the management of both production and environment in order to reach thermal comfort and animal welfare. The understanding of animal behavior through the use of image analysis may be an efficient method for estimating welfare in a non-invasive way. Among the systems and techniques used in controlling process, computer vision and image processing have been studied and applied in the animal production process as well as in final product processing. This research had the objective to develop an algorithm using computational vision, to recognize animal behavior data and identify piglets thermal comfort and welfare status. The software was validated in a commercial swine farrowing house. The developed algorithm automatically found the centre of mass of each animal, the dispersion of the piglets and their occupied area. Based on these results it was possible through the image analysis, characterize different piglets behavior patterns inside the farrowing house facilities, based on the dispersion of their centre of mass in different environment conditions.