  Counting objects in images is a pattern recognition problem that focuses on
identifying an element to determine its incidence and is approached in the
literature as Visual Object Counting (VOC). In this work, we propose a
methodology to count wood logs. First, wood logs are segmented from the image
background. This first segmentation step is obtained using the Pix2Pix
framework that implements Conditional Generative Adversarial Networks (CGANs).
Second, the clusters are counted using Connected Components. The average
accuracy of the segmentation exceeds 89% while the average amount of wood logs
identified based on total accounted is over 97%.
