  Deep convolutional neural network (DCNN) is the state-of-the-art method for
image segmentation, which is one of key challenging computer vision tasks.
However, DCNN requires a lot of training images with corresponding image masks
to get a good segmentation result. Image annotation software which is easy to
use and allows fast image mask generation is in great demand. To the best of
our knowledge, all existing image annotation software support only drawing
bounding polygons, bounding boxes, or bounding ellipses to mark target objects.
These existing software are inefficient when targeting objects that have
irregular shapes (e.g., defects in fabric images or tire images). In this paper
we design an easy-to-use image annotation software called Mask Editor for image
mask generation. Mask Editor allows drawing any bounding curve to mark objects
and improves efficiency to mark objects with irregular shapes. Mask Editor also
supports drawing bounding polygons, drawing bounding boxes, drawing bounding
ellipses, painting, erasing, super-pixel-marking, image cropping, multi-class
masks, mask loading, and mask modifying.
