This study proposes an algorithm for semantic segmentation of targets in images based on fully convolutional neural networks and a new method to make and augment dataset. The algorithm primarily segments the targets from images using improved fully convolutional neural networks, OTSU method is applied to binarize images and segment the general areas of targets, finally, the fully connected conditional random field algorithm is used to correct the general areas of targets and get the final results. This algorithm achieves the accuracy of 85.7% and speed of 0.181 second per image on test set, and prepares for further analysis of targets in images.