  In the emerging advancement in the branch of autonomous robotics, the ability
of a robot to efficiently localize and construct maps of its surrounding is
crucial. This paper deals with utilizing thermal-infrared cameras, as opposed
to conventional cameras as the primary sensor to capture images of the robot's
surroundings. For localization, the images need to be further processed before
feeding them to a navigational system. The main motivation of this paper was to
develop an edge detection methodology capable of utilizing the low-SNR poor
output from such a thermal camera and effectively detect smooth edges of the
surrounding environment. The enhanced edge detector proposed in this paper
takes the raw image from the thermal sensor, denoises the images, applies Canny
edge detection followed by CSS method. The edges are ranked to remove any noise
and only edges of the highest rank are kept. Then, the broken edges are linked
by computing edge metrics and a smooth edge of the surrounding is displayed in
a binary image. Several comparisons are also made in the paper between the
proposed technique and the existing techniques.
