  Corner detection is a vital operation in numerous computer vision
applications. The Chord-to-Point Distance Accumulation (CPDA) detector is
recognized as the contour-based corner detector producing the lowest
localization error while localizing corners in an image. However, in our
experiment part, we demonstrate that CPDA detector often misses some potential
corners. Moreover, the detection algorithm of CPDA is computationally costly.
In this paper, We focus on reducing localization error as well as increasing
average repeatability. The preprocessing and refinements steps of proposed
process are similar to CPDA. Our experimental results will show the
effectiveness and robustness of proposed process over CPDA.
