  Peoples nowadays prefer to use digital gadgets like cameras or mobile phones
for capturing documents. Automatic extraction of panels/characters from the
images of a comic document is challenging due to the wide variety of drawing
styles adopted by writers, beneficial for readers to read them on mobile
devices at any time and useful for automatic digitization. Most of the methods
for localization of panel/character rely on the connected component analysis or
page background mask and are applicable only for a limited comic dataset. This
work proposes a panel/character localization architecture based on the features
of YOLO and CNN for extraction of both panels and characters from comic book
images. The method achieved remarkable results on Bengali Comic Book Image
dataset (BCBId) consisting of total $4130$ images, developed by us as well as
on a variety of publicly available comic datasets in other languages, i.e.
eBDtheque, Manga 109 and DCM dataset.
